PADDI enrichment analysis - Reactome

Introduction

Let’s do some enrichment analysis.

suppressPackageStartupMessages({
  library("gplots")
  library("reshape2")
  library("WGCNA")
  library("dplyr")
  library("DESeq2")
  library("mitch")
  library("MASS")
  library("kableExtra")
  library("ggplot2")
  library("eulerr")
  library("DT")
  library("xlsx")
  library("RhpcBLASctl")
})

load("qc.Rds")

RhpcBLASctl::blas_set_num_threads(1)

knitr::opts_chunk$set(dev = 'svg') # set output device to svg

Load REACTOME gene sets

reactome <- mitch::gmt_import("ReactomePathways_30oct24.gmt")

Gene table

gt <- read.table("../ref/gencode.v38.genetable.tsv")

rownames(gt) <- paste(gt[,1],gt[,2])

gt[,1] <- rownames(gt)

Individual contrast analysis unstratified

Start with Reactome gene sets

Firstly we do the unstratified contrasts.

• crp_t0_adj
• crp_eos_adj
• crp_pod1_adj
• dex_t0_adj
• dex_eos_adj
• dex_pod1_adj

de <- crp_t0_adj
myname <- "crp_t0_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21935

## Note: no. genes in output = 21870

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

m_crp_t0_adj <- mres
mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

crp_t0_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
317	Cytochrome c-mediated apoptotic response	13	0.0006672	-0.5449935	0.0088820
454	ER Quality Control Compartment (ERQC)	21	0.0001924	-0.4699594	0.0034016
104	Antigen Presentation: Folding, assembly and peptide loading of class I MHC	30	0.0000104	-0.4649512	0.0003645
217	Calnexin/calreticulin cycle	26	0.0000696	-0.4506113	0.0015405
958	N-glycan trimming in the ER and Calnexin/Calreticulin cycle	35	0.0000052	-0.4448310	0.0002191
661	Golgi Associated Vesicle Biogenesis	55	0.0000010	-0.3805880	0.0000590
657	Glycosphingolipid catabolism	31	0.0004122	-0.3664959	0.0061983
848	MAPK targets/ Nuclear events mediated by MAP kinases	31	0.0006577	-0.3534739	0.0088820
1236	RHO GTPases Activate WASPs and WAVEs	35	0.0003129	-0.3519997	0.0051101
1927	trans-Golgi Network Vesicle Budding	69	0.0000015	-0.3348716	0.0000825
354	Defective CFTR causes cystic fibrosis	47	0.0000763	-0.3334399	0.0016346
72	Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	59	0.0000108	-0.3311041	0.0003728
1443	Ribosomal scanning and start codon recognition	58	0.0000182	-0.3253050	0.0005746
1799	Translation initiation complex formation	58	0.0000186	-0.3249603	0.0005770
1485	SRP-dependent cotranslational protein targeting to membrane	110	0.0000000	-0.3195112	0.0000007
456	ER-Phagosome pathway	75	0.0000033	-0.3106884	0.0001536
844	MAP kinase activation	63	0.0000233	-0.3081485	0.0006846
690	Hedgehog ligand biogenesis	47	0.0003800	-0.2995600	0.0059061
812	L13a-mediated translational silencing of Ceruloplasmin expression	109	0.0000001	-0.2954081	0.0000080
114	Apoptotic execution phase	46	0.0005451	-0.2946138	0.0078976
616	GTP hydrolysis and joining of the 60S ribosomal subunit	110	0.0000001	-0.2941410	0.0000080
901	Metabolism of polyamines	46	0.0006166	-0.2917729	0.0085479
1543	Signaling by BRAF and RAF1 fusions	60	0.0001200	-0.2870289	0.0023604
569	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0003999	-0.2865150	0.0061645
218	Cap-dependent Translation Initiation	117	0.0000001	-0.2850767	0.0000080
493	Eukaryotic Translation Initiation	117	0.0000001	-0.2850767	0.0000080
772	Interleukin-17 signaling	68	0.0000492	-0.2846285	0.0011556
1159	Platelet degranulation	105	0.0000005	-0.2829379	0.0000338
1044	Nuclear Events (kinase and transcription factor activation)	54	0.0003242	-0.2827877	0.0052056
1434	Response to elevated platelet cytosolic Ca2+	109	0.0000004	-0.2820394	0.0000240

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/crp_t0_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

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## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e7c7c7f5f.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- crp_eos_adj
myname <- "crp_eos_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 22067

## Note: no. genes in output = 21999

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

m_crp_eos_adj <- mres
mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

crp_eos_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
550	Formation of ATP by chemiosmotic coupling	20	0.0000000	-0.8530097	0.0000000
1127	Peptide chain elongation	88	0.0000000	-0.8425500	0.0000000
559	Formation of a pool of free 40S subunits	100	0.0000000	-0.8424586	0.0000000
495	Eukaryotic Translation Elongation	93	0.0000000	-0.8344461	0.0000000
1867	Viral mRNA Translation	88	0.0000000	-0.8310738	0.0000000
815	L13a-mediated translational silencing of Ceruloplasmin expression	110	0.0000000	-0.8264234	0.0000000
946	Modulation by Mtb of host immune system	7	0.0001529	-0.8262745	0.0008767
619	GTP hydrolysis and joining of the 60S ribosomal subunit	111	0.0000000	-0.8220128	0.0000000
1454	SARS-CoV-1 modulates host translation machinery	36	0.0000000	-0.8190467	0.0000000
220	Cap-dependent Translation Initiation	118	0.0000000	-0.8166167	0.0000000
496	Eukaryotic Translation Initiation	118	0.0000000	-0.8166167	0.0000000
572	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0000000	-0.8125909	0.0000000
497	Eukaryotic Translation Termination	92	0.0000000	-0.8098801	0.0000000
934	Mitochondrial translation initiation	90	0.0000000	-0.8069794	0.0000000
1487	SRP-dependent cotranslational protein targeting to membrane	111	0.0000000	-0.8054049	0.0000000
1514	Selenocysteine synthesis	92	0.0000000	-0.8045731	0.0000000
1039	Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	94	0.0000000	-0.8021981	0.0000000
73	Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	59	0.0000000	-0.7962038	0.0000000
933	Mitochondrial translation elongation	90	0.0000000	-0.7937134	0.0000000
1803	Translation initiation complex formation	58	0.0000000	-0.7930814	0.0000000
1445	Ribosomal scanning and start codon recognition	58	0.0000000	-0.7914203	0.0000000
935	Mitochondrial translation termination	90	0.0000000	-0.7834599	0.0000000
932	Mitochondrial translation	96	0.0000000	-0.7762502	0.0000000
1433	Response of EIF2AK4 (GCN2) to amino acid deficiency	100	0.0000000	-0.7641153	0.0000000
291	Complex III assembly	23	0.0000000	-0.7620645	0.0000000
1143	Phosphate bond hydrolysis by NUDT proteins	7	0.0005944	-0.7494543	0.0029675
1802	Translation	293	0.0000000	-0.7315663	0.0000000
1460	SARS-CoV-2 modulates host translation machinery	49	0.0000000	-0.7302310	0.0000000
504	FASTK family proteins regulate processing and stability of mitochondrial RNAs	19	0.0000000	-0.7269863	0.0000004
1513	Selenoamino acid metabolism	115	0.0000000	-0.7127558	0.0000000

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/crp_eos_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

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## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e514b2379.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- crp_pod1_adj
myname <- "crp_pod1_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21313

## Note: no. genes in output = 21253

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

m_crp_pod1_adj <- mres
mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

crp_pod1_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
178	CD163 mediating an anti-inflammatory response	8	0.0000191	0.8726171	0.0003500
749	Insulin-like Growth Factor-2 mRNA Binding Proteins (IGF2BPs/IMPs/VICKZs) bind RNA	6	0.0005538	0.8139973	0.0062578
962	NFE2L2 regulates pentose phosphate pathway genes	8	0.0005941	0.7010944	0.0065974
554	Formation of a pool of free 40S subunits	100	0.0000000	-0.6858006	0.0000000
1120	Peptide chain elongation	88	0.0000000	-0.6830735	0.0000000
490	Eukaryotic Translation Elongation	93	0.0000000	-0.6712269	0.0000000
1507	Selenocysteine synthesis	92	0.0000000	-0.6661198	0.0000000
1856	Viral mRNA Translation	88	0.0000000	-0.6576209	0.0000000
1447	SARS-CoV-1 modulates host translation machinery	36	0.0000000	-0.6564809	0.0000000
492	Eukaryotic Translation Termination	92	0.0000000	-0.6545162	0.0000000
567	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0000000	-0.6435538	0.0000000
809	L13a-mediated translational silencing of Ceruloplasmin expression	110	0.0000000	-0.6423248	0.0000000
1033	Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	94	0.0000000	-0.6370419	0.0000000
613	GTP hydrolysis and joining of the 60S ribosomal subunit	111	0.0000000	-0.6301576	0.0000000
216	Cap-dependent Translation Initiation	118	0.0000000	-0.6262726	0.0000000
491	Eukaryotic Translation Initiation	118	0.0000000	-0.6262726	0.0000000
72	Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	59	0.0000000	-0.5977739	0.0000000
1793	Translation initiation complex formation	58	0.0000000	-0.5923778	0.0000000
1426	Response of EIF2AK4 (GCN2) to amino acid deficiency	100	0.0000000	-0.5868378	0.0000000
1438	Ribosomal scanning and start codon recognition	58	0.0000000	-0.5786889	0.0000000
1661	Synthesis of Leukotrienes (LT) and Eoxins (EX)	15	0.0001054	0.5782214	0.0016062
928	Mitochondrial translation initiation	90	0.0000000	-0.5682570	0.0000000
1480	SRP-dependent cotranslational protein targeting to membrane	111	0.0000000	-0.5647526	0.0000000
927	Mitochondrial translation elongation	90	0.0000000	-0.5594355	0.0000000
598	GAB1 signalosome	14	0.0003153	0.5559920	0.0040380
1506	Selenoamino acid metabolism	115	0.0000000	-0.5559006	0.0000000
1453	SARS-CoV-2 modulates host translation machinery	49	0.0000000	-0.5516691	0.0000000
929	Mitochondrial translation termination	90	0.0000000	-0.5505038	0.0000000
926	Mitochondrial translation	96	0.0000000	-0.5501637	0.0000000
1032	Nonsense Mediated Decay (NMD) enhanced by the Exon Junction Complex (EJC)	114	0.0000000	-0.5420803	0.0000000

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/crp_pod1_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

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## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e9ca628f.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

## dex
de <- dex_t0_adj
myname <- "dex_t0_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21935

## Note: no. genes in output = 21870

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

m_dex_t0_adj <- mres
mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

dex_t0_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
1361	Regulation of NFE2L2 gene expression	8	0.0000287	-0.8540733	0.0007563
984	NR1H2 & NR1H3 regulate gene expression to control bile acid homeostasis	7	0.0005220	-0.7570978	0.0075302
777	Interleukin-21 signaling	9	0.0002255	-0.7099452	0.0042146
419	Disorders of Developmental Biology	12	0.0002036	-0.6191860	0.0039240
420	Disorders of Nervous System Development	12	0.0002036	-0.6191860	0.0039240
837	Loss of function of MECP2 in Rett syndrome	12	0.0002036	-0.6191860	0.0039240
1130	Pervasive developmental disorders	12	0.0002036	-0.6191860	0.0039240
987	NR1H3 & NR1H2 regulate gene expression linked to cholesterol transport and efflux	32	0.0000000	-0.5723853	0.0000017
1192	Processive synthesis on the C-strand of the telomere	19	0.0000532	-0.5354085	0.0013319
1416	Removal of the Flap Intermediate from the C-strand	17	0.0001492	-0.5311991	0.0031371
986	NR1H2 and NR1H3-mediated signaling	38	0.0000000	-0.5174201	0.0000024
673	HDMs demethylate histones	22	0.0000630	-0.4926954	0.0014995
1724	TP53 Regulates Transcription of Genes Involved in G2 Cell Cycle Arrest	18	0.0003072	-0.4913051	0.0053096
1378	Regulation of TP53 Activity through Acetylation	29	0.0000154	-0.4636314	0.0004878
1535	Signaling by ALK	24	0.0002712	-0.4293311	0.0048393
497	Expression and translocation of olfactory receptors	52	0.0000001	0.4240976	0.0000061
1497	SUMOylation of DNA replication proteins	46	0.0000011	-0.4154481	0.0000475
180	CD22 mediated BCR regulation	59	0.0000001	-0.4045797	0.0000046
686	HSF1-dependent transactivation	30	0.0001309	-0.4033974	0.0028664
591	G0 and Early G1	27	0.0003421	-0.3981155	0.0055395
1080	PD-1 signaling	28	0.0003336	-0.3916635	0.0054950
1355	Regulation of MECP2 expression and activity	29	0.0002918	-0.3885874	0.0051595
273	Classical antibody-mediated complement activation	70	0.0000000	-0.3823630	0.0000023
1063	Olfactory Signaling Pathway	57	0.0000008	0.3781979	0.0000358
1045	Nuclear Pore Complex (NPC) Disassembly	36	0.0001134	-0.3716935	0.0025406
1446	Role of phospholipids in phagocytosis	89	0.0000000	-0.3709341	0.0000001
1508	Scavenging of heme from plasma	71	0.0000001	-0.3693870	0.0000045
342	DNA strand elongation	32	0.0003231	-0.3672555	0.0054614
507	FCGR activation	77	0.0000000	-0.3670075	0.0000020
595	G1/S-Specific Transcription	29	0.0006803	-0.3644538	0.0089790

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/dex_t0_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
## 2/36 [checklibraries]            
## 3/36                             
## 4/36 [peek]                      
## 5/36                             
## 6/36 [metrics]                   
## 7/36                             
## 8/36 [scatterplot]

## 9/36                             
## 10/36 [contourplot]               
## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e3be8c96.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- dex_eos_adj
myname <- "dex_eos_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 22067

## Note: no. genes in output = 21999

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

m_dex_eos_adj <- mres
mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

dex_eos_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
180	CD163 mediating an anti-inflammatory response	9	0.0000937	0.7518468	0.0035494
504	FASTK family proteins regulate processing and stability of mitochondrial RNAs	19	0.0000002	0.6869930	0.0000139
924	Mitochondrial RNA degradation	25	0.0000002	0.6015728	0.0000137
1814	Translocation of ZAP-70 to Immunological synapse	24	0.0000005	-0.5944444	0.0000254
1419	Replacement of protamines by nucleosomes in the male pronucleus	13	0.0002912	0.5802644	0.0095353
1930	tRNA processing in the mitochondrion	24	0.0000016	0.5660978	0.0000741
182	CD22 mediated BCR regulation	58	0.0000000	0.5129462	0.0000000
1268	RNA Polymerase I Promoter Opening	17	0.0003006	0.5063153	0.0096806
1082	PD-1 signaling	28	0.0000037	-0.5049741	0.0001714
263	Chromatin modifications during the maternal to zygotic transition (MZT)	23	0.0000324	0.5005085	0.0013908
1149	Phosphorylation of CD3 and TCR zeta chains	27	0.0000070	-0.4994707	0.0003152
43	Activated PKN1 stimulates transcription of AR (androgen receptor) regulated genes KLK2 and KLK3	20	0.0002640	0.4711657	0.0087927
275	Classical antibody-mediated complement activation	69	0.0000000	0.4575943	0.0000000
1510	Scavenging of heme from plasma	70	0.0000000	0.4526739	0.0000000
1923	rRNA processing in the mitochondrion	24	0.0001795	0.4416875	0.0063070
309	Creation of C4 and C2 activators	71	0.0000000	0.4225917	0.0000001
1243	RHO GTPases activate PKNs	46	0.0000011	0.4149151	0.0000553
1447	Role of LAT2/NTAL/LAB on calcium mobilization	77	0.0000000	0.4121377	0.0000001
100	Amyloid fiber formation	52	0.0000004	0.4064486	0.0000224
510	FCGR activation	76	0.0000000	0.4045523	0.0000002
1345	Regulation of Complement cascade	96	0.0000000	0.3889545	0.0000000
635	Generation of second messenger molecules	38	0.0000491	-0.3805310	0.0019754
160	Binding and Uptake of Ligands by Scavenger Receptors	94	0.0000000	0.3662488	0.0000001
106	Antigen activates B Cell Receptor (BCR) leading to generation of second messengers	83	0.0000000	0.3559033	0.0000019
745	Initial triggering of complement	79	0.0000001	0.3546233	0.0000044
289	Complement cascade	100	0.0000000	0.3454751	0.0000003
512	FCGR3A-mediated phagocytosis	121	0.0000000	0.3295918	0.0000001
829	Leishmania phagocytosis	121	0.0000000	0.3295918	0.0000001
1121	Parasite infection	121	0.0000000	0.3295918	0.0000001
1448	Role of phospholipids in phagocytosis	88	0.0000003	0.3143015	0.0000201

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/dex_eos_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
## 2/36 [checklibraries]            
## 3/36                             
## 4/36 [peek]                      
## 5/36                             
## 6/36 [metrics]                   
## 7/36                             
## 8/36 [scatterplot]

## 9/36                             
## 10/36 [contourplot]               
## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e77049f80.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- dex_pod1_adj
myname <- "dex_pod1_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21313

## Note: no. genes in output = 21253

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

m_dex_pod1_adj <- mres
mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

dex_pod1_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
67	Activation of caspases through apoptosome-mediated cleavage	6	0.0009256	-0.7807534	0.0075023
57	Activation of NIMA Kinases NEK9, NEK6, NEK7	7	0.0011691	-0.7084762	0.0089118
574	Fructose metabolism	7	0.0012723	0.7032046	0.0096222
484	Establishment of Sister Chromatid Cohesion	11	0.0000748	-0.6895345	0.0009208
1346	Regulation of IFNA/IFNB signaling	12	0.0000463	-0.6790484	0.0006304
774	Interleukin-21 signaling	9	0.0006451	-0.6567083	0.0055079
175	Butyrophilin (BTN) family interactions	10	0.0006208	0.6249306	0.0053480
782	Interleukin-6 signaling	10	0.0010825	-0.5967801	0.0084535
1374	Regulation of TP53 Activity through Association with Co-factors	11	0.0006608	0.5928991	0.0056172
289	Condensation of Prometaphase Chromosomes	11	0.0011605	-0.5655862	0.0088832
939	Mitotic Telophase/Cytokinesis	13	0.0004214	-0.5647834	0.0037828
1156	Platelet sensitization by LDL	16	0.0002588	-0.5274639	0.0024986
318	Cytosolic iron-sulfur cluster assembly	13	0.0013146	0.5145806	0.0098646
1365	Regulation of RUNX1 Expression and Activity	18	0.0002791	-0.4946864	0.0026804
773	Interleukin-20 family signaling	17	0.0004751	-0.4894740	0.0042249
505	FCGR activation	76	0.0000000	-0.4656840	0.0000000
180	CD22 mediated BCR regulation	58	0.0000000	-0.4582831	0.0000001
1599	Signaling by PDGFR in disease	19	0.0005860	-0.4555455	0.0051165
588	G0 and Early G1	27	0.0000439	-0.4542019	0.0006071
1440	Role of LAT2/NTAL/LAB on calcium mobilization	77	0.0000000	-0.4464476	0.0000000
759	Interferon alpha/beta signaling	63	0.0000000	-0.4375499	0.0000001
592	G1/S-Specific Transcription	29	0.0000454	-0.4374553	0.0006231
1503	Scavenging of heme from plasma	70	0.0000000	-0.4290867	0.0000000
1768	Transcription of E2F targets under negative control by DREAM complex	19	0.0012429	-0.4278342	0.0094375
105	Antigen activates B Cell Receptor (BCR) leading to generation of second messengers	83	0.0000000	-0.4243605	0.0000000
507	FCGR3A-mediated phagocytosis	121	0.0000000	-0.4238482	0.0000000
823	Leishmania phagocytosis	121	0.0000000	-0.4238482	0.0000000
1114	Parasite infection	121	0.0000000	-0.4238482	0.0000000
502	FCERI mediated Ca+2 mobilization	92	0.0000000	-0.4218949	0.0000000
1228	RHO GTPases Activate NADPH Oxidases	21	0.0009063	-0.4182187	0.0073772

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/dex_pod1_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
## 2/36 [checklibraries]            
## 3/36                             
## 4/36 [peek]                      
## 5/36                             
## 6/36 [metrics]                   
## 7/36                             
## 8/36 [scatterplot]

## 9/36                             
## 10/36 [contourplot]               
## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e41c9778e.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

Now take a look at the interactions.

• m_crp_t0_adj
• m_crp_eos_adj
• m_crp_pod1_adj
• m_dex_t0_adj
• m_dex_eos_adj
• m_dex_pod1_adj

m_crp_t0_adj_up <- subset(m_crp_t0_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist>0)$set
m_crp_t0_adj_dn <- subset(m_crp_t0_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist<0)$set

m_crp_eos_adj_up <- subset(m_crp_eos_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist>0)$set
m_crp_eos_adj_dn <- subset(m_crp_eos_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist<0)$set

m_crp_pod1_adj_up <- subset(m_crp_pod1_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist>0)$set
m_crp_pod1_adj_dn <- subset(m_crp_pod1_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist<0)$set

m_dex_t0_adj_up <- subset(m_dex_t0_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist>0)$set
m_dex_t0_adj_dn <- subset(m_dex_t0_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist<0)$set

m_dex_eos_adj_up <- subset(m_dex_eos_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist>0)$set
m_dex_eos_adj_dn <- subset(m_dex_eos_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist<0)$set

m_dex_pod1_adj_up <- subset(m_dex_pod1_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist>0)$set
m_dex_pod1_adj_dn <- subset(m_dex_pod1_adj$enrichment_result,p.adjustANOVA<0.01 & s.dist<0)$set

# CRP
crp_l <- list("t0 CRP up"=m_crp_t0_adj_up,"t0 CRP dn"=m_crp_t0_adj_dn,
  "EOS CRP up"=m_crp_eos_adj_up, "EOS CRP dn"=m_crp_eos_adj_dn,
  "POD1 CRP up"=m_crp_pod1_adj_up, "POD1 CRP dn"=m_crp_pod1_adj_dn)

plot(euler(crp_l),quantities = TRUE)

crp_l <- list("t0 CRP up"=m_crp_t0_adj_up,"t0 CRP dn"=m_crp_t0_adj_dn,
  "EOS CRP up"=m_crp_eos_adj_up, "EOS CRP dn"=m_crp_eos_adj_dn)

plot(euler(crp_l),quantities = TRUE)

intersect(m_crp_t0_adj_dn, m_crp_eos_adj_dn)

##  [1] "N-glycan trimming in the ER and Calnexin/Calreticulin cycle"                                           
##  [2] "Glycosphingolipid catabolism"                                                                          
##  [3] "trans-Golgi Network Vesicle Budding"                                                                   
##  [4] "Defective CFTR causes cystic fibrosis"                                                                 
##  [5] "Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S"
##  [6] "Ribosomal scanning and start codon recognition"                                                        
##  [7] "Translation initiation complex formation"                                                              
##  [8] "SRP-dependent cotranslational protein targeting to membrane"                                           
##  [9] "ER-Phagosome pathway"                                                                                  
## [10] "Hedgehog ligand biogenesis"                                                                            
## [11] "L13a-mediated translational silencing of Ceruloplasmin expression"                                     
## [12] "GTP hydrolysis and joining of the 60S ribosomal subunit"                                               
## [13] "Metabolism of polyamines"                                                                              
## [14] "Formation of the ternary complex, and subsequently, the 43S complex"                                   
## [15] "Cap-dependent Translation Initiation"                                                                  
## [16] "Eukaryotic Translation Initiation"                                                                     
## [17] "Platelet degranulation"                                                                                
## [18] "Response to elevated platelet cytosolic Ca2+"                                                          
## [19] "ABC transporter disorders"                                                                             
## [20] "Antigen processing-Cross presentation"                                                                 
## [21] "Formation of a pool of free 40S subunits"                                                              
## [22] "Selenoamino acid metabolism"                                                                           
## [23] "Protein ubiquitination"                                                                                
## [24] "MAPK6/MAPK4 signaling"                                                                                 
## [25] "Mitochondrial protein degradation"                                                                     
## [26] "Viral mRNA Translation"                                                                                
## [27] "Response of EIF2AK4 (GCN2) to amino acid deficiency"                                                   
## [28] "Peptide chain elongation"                                                                              
## [29] "Interleukin-1 signaling"                                                                               
## [30] "Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)"                          
## [31] "Selenocysteine synthesis"                                                                              
## [32] "Translation"                                                                                           
## [33] "Eukaryotic Translation Termination"                                                                    
## [34] "TP53 Regulates Metabolic Genes"                                                                        
## [35] "Eukaryotic Translation Elongation"                                                                     
## [36] "Influenza Infection"                                                                                   
## [37] "Signaling by ROBO receptors"                                                                           
## [38] "Regulation of expression of SLITs and ROBOs"                                                           
## [39] "Mitotic Prophase"                                                                                      
## [40] "Protein localization"                                                                                  
## [41] "Cellular response to starvation"                                                                       
## [42] "Asparagine N-linked glycosylation"                                                                     
## [43] "Influenza Viral RNA Transcription and Replication"                                                     
## [44] "Ub-specific processing proteases"                                                                      
## [45] "Apoptosis"                                                                                             
## [46] "Nonsense Mediated Decay (NMD) enhanced by the Exon Junction Complex (EJC)"                             
## [47] "Nonsense-Mediated Decay (NMD)"                                                                         
## [48] "Metabolism of amino acids and derivatives"                                                             
## [49] "Innate Immune System"                                                                                  
## [50] "HIV Infection"                                                                                         
## [51] "Platelet activation, signaling and aggregation"                                                        
## [52] "Host Interactions of HIV factors"                                                                      
## [53] "Class I MHC mediated antigen processing & presentation"                                                
## [54] "Macroautophagy"                                                                                        
## [55] "SARS-CoV-2 Infection"                                                                                  
## [56] "SARS-CoV-2-host interactions"                                                                          
## [57] "Aerobic respiration and respiratory electron transport"                                                
## [58] "Metabolism of proteins"                                                                                
## [59] "Autophagy"                                                                                             
## [60] "Programmed Cell Death"                                                                                 
## [61] "Cellular responses to stimuli"                                                                         
## [62] "Cellular responses to stress"                                                                          
## [63] "Neddylation"                                                                                           
## [64] "rRNA processing in the nucleus and cytosol"                                                            
## [65] "HIV Life Cycle"                                                                                        
## [66] "Post-translational protein modification"                                                               
## [67] "Major pathway of rRNA processing in the nucleolus and cytosol"                                         
## [68] "Respiratory electron transport"                                                                        
## [69] "Membrane Trafficking"                                                                                  
## [70] "Transport to the Golgi and subsequent modification"                                                    
## [71] "Mitotic Anaphase"                                                                                      
## [72] "rRNA processing"                                                                                       
## [73] "Mitotic Metaphase and Anaphase"                                                                        
## [74] "Infectious disease"                                                                                    
## [75] "Cellular response to chemical stress"                                                                  
## [76] "Intra-Golgi and retrograde Golgi-to-ER traffic"                                                        
## [77] "Metabolism of RNA"                                                                                     
## [78] "Processing of Capped Intron-Containing Pre-mRNA"                                                       
## [79] "Viral Infection Pathways"                                                                              
## [80] "Antigen processing: Ubiquitination & Proteasome degradation"                                           
## [81] "Metabolism"                                                                                            
## [82] "Vesicle-mediated transport"                                                                            
## [83] "Disease"                                                                                               
## [84] "Cell Cycle Checkpoints"                                                                                
## [85] "M Phase"                                                                                               
## [86] "Immune System"                                                                                         
## [87] "RHO GTPase Effectors"                                                                                  
## [88] "Nervous system development"                                                                            
## [89] "Transcriptional Regulation by TP53"                                                                    
## [90] "Axon guidance"                                                                                         
## [91] "SARS-CoV Infections"                                                                                   
## [92] "Adaptive Immune System"                                                                                
## [93] "Developmental Biology"

intersect(m_crp_t0_adj_up, m_crp_eos_adj_up)

## character(0)

crp_l <- list("EOS CRP up"=m_crp_eos_adj_up, "EOS CRP dn"=m_crp_eos_adj_dn,
  "POD1 CRP up"=m_crp_pod1_adj_up, "POD1 CRP dn"=m_crp_pod1_adj_dn)

plot(euler(crp_l),quantities = TRUE)

pdf("pw_euler_crp.pdf",width=5,height=5)
plot(euler(crp_l),quantities = TRUE)
dev.off()

## svg 
##   2

intersect(m_crp_eos_adj_dn, m_crp_pod1_adj_dn)

##  [1] "Peptide chain elongation"                                                                              
##  [2] "Formation of a pool of free 40S subunits"                                                              
##  [3] "Eukaryotic Translation Elongation"                                                                     
##  [4] "Viral mRNA Translation"                                                                                
##  [5] "L13a-mediated translational silencing of Ceruloplasmin expression"                                     
##  [6] "GTP hydrolysis and joining of the 60S ribosomal subunit"                                               
##  [7] "SARS-CoV-1 modulates host translation machinery"                                                       
##  [8] "Cap-dependent Translation Initiation"                                                                  
##  [9] "Eukaryotic Translation Initiation"                                                                     
## [10] "Formation of the ternary complex, and subsequently, the 43S complex"                                   
## [11] "Eukaryotic Translation Termination"                                                                    
## [12] "Mitochondrial translation initiation"                                                                  
## [13] "SRP-dependent cotranslational protein targeting to membrane"                                           
## [14] "Selenocysteine synthesis"                                                                              
## [15] "Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)"                          
## [16] "Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S"
## [17] "Mitochondrial translation elongation"                                                                  
## [18] "Translation initiation complex formation"                                                              
## [19] "Ribosomal scanning and start codon recognition"                                                        
## [20] "Mitochondrial translation termination"                                                                 
## [21] "Mitochondrial translation"                                                                             
## [22] "Response of EIF2AK4 (GCN2) to amino acid deficiency"                                                   
## [23] "Complex III assembly"                                                                                  
## [24] "Translation"                                                                                           
## [25] "SARS-CoV-2 modulates host translation machinery"                                                       
## [26] "Selenoamino acid metabolism"                                                                           
## [27] "Nonsense Mediated Decay (NMD) enhanced by the Exon Junction Complex (EJC)"                             
## [28] "Nonsense-Mediated Decay (NMD)"                                                                         
## [29] "Major pathway of rRNA processing in the nucleolus and cytosol"                                         
## [30] "rRNA processing"                                                                                       
## [31] "Regulation of expression of SLITs and ROBOs"                                                           
## [32] "Complex I biogenesis"                                                                                  
## [33] "rRNA processing in the nucleus and cytosol"                                                            
## [34] "Mitochondrial protein import"                                                                          
## [35] "Respiratory electron transport"                                                                        
## [36] "Influenza Viral RNA Transcription and Replication"                                                     
## [37] "Cellular response to starvation"                                                                       
## [38] "Mitochondrial protein degradation"                                                                     
## [39] "Influenza Infection"                                                                                   
## [40] "rRNA modification in the nucleus and cytosol"                                                          
## [41] "Aerobic respiration and respiratory electron transport"                                                
## [42] "Complex IV assembly"                                                                                   
## [43] "Signaling by ROBO receptors"                                                                           
## [44] "Protein localization"                                                                                  
## [45] "Mitochondrial Fatty Acid Beta-Oxidation"                                                               
## [46] "mRNA Splicing - Minor Pathway"                                                                         
## [47] "Metabolism of amino acids and derivatives"                                                             
## [48] "Metabolism of RNA"                                                                                     
## [49] "tRNA modification in the nucleus and cytosol"                                                          
## [50] "Formation of TC-NER Pre-Incision Complex"                                                              
## [51] "tRNA processing"                                                                                       
## [52] "Transcription-Coupled Nucleotide Excision Repair (TC-NER)"                                             
## [53] "SARS-CoV-1-host interactions"                                                                          
## [54] "mRNA Splicing"                                                                                         
## [55] "mRNA Splicing - Major Pathway"                                                                         
## [56] "Resolution of Abasic Sites (AP sites)"                                                                 
## [57] "Global Genome Nucleotide Excision Repair (GG-NER)"                                                     
## [58] "Dual incision in TC-NER"                                                                               
## [59] "Gap-filling DNA repair synthesis and ligation in TC-NER"                                               
## [60] "Nucleotide Excision Repair"                                                                            
## [61] "RNA Polymerase II Transcription Termination"                                                           
## [62] "Processing of Capped Intron-Containing Pre-mRNA"                                                       
## [63] "Viral Infection Pathways"                                                                              
## [64] "Metabolism of non-coding RNA"                                                                          
## [65] "snRNP Assembly"                                                                                        
## [66] "Metabolism of proteins"                                                                                
## [67] "tRNA processing in the nucleus"                                                                        
## [68] "DNA Repair"                                                                                            
## [69] "Transport of Mature Transcript to Cytoplasm"                                                           
## [70] "SARS-CoV-2-host interactions"                                                                          
## [71] "Metabolism"                                                                                            
## [72] "Transport of Mature mRNA derived from an Intron-Containing Transcript"

intersect(m_crp_eos_adj_up, m_crp_pod1_adj_up)

## [1] "Interleukin-10 signaling"                  
## [2] "Interleukin-4 and Interleukin-13 signaling"
## [3] "RAC1 GTPase cycle"                         
## [4] "GPCR ligand binding"                       
## [5] "Neuronal System"                           
## [6] "Signaling by GPCR"                         
## [7] "GPCR downstream signalling"

intersect(m_crp_eos_adj_up, m_crp_pod1_adj_dn)

## character(0)

intersect(m_crp_eos_adj_dn, m_crp_pod1_adj_up)

##  [1] "Binding and Uptake of Ligands by Scavenger Receptors"                              
##  [2] "Role of LAT2/NTAL/LAB on calcium mobilization"                                     
##  [3] "Platelet degranulation"                                                            
##  [4] "Response to elevated platelet cytosolic Ca2+"                                      
##  [5] "Antigen activates B Cell Receptor (BCR) leading to generation of second messengers"
##  [6] "FCERI mediated MAPK activation"                                                    
##  [7] "Nuclear events mediated by NFE2L2"                                                 
##  [8] "FCGR3A-mediated phagocytosis"                                                      
##  [9] "Leishmania phagocytosis"                                                           
## [10] "Parasite infection"                                                                
## [11] "Signaling by the B Cell Receptor (BCR)"                                            
## [12] "FCERI mediated Ca+2 mobilization"                                                  
## [13] "Regulation of actin dynamics for phagocytic cup formation"                         
## [14] "KEAP1-NFE2L2 pathway"                                                              
## [15] "Fc epsilon receptor (FCERI) signaling"                                             
## [16] "Cell surface interactions at the vascular wall"                                    
## [17] "FCGR3A-mediated IL10 synthesis"                                                    
## [18] "Anti-inflammatory response favouring Leishmania parasite infection"                
## [19] "Leishmania parasite growth and survival"                                           
## [20] "Fcgamma receptor (FCGR) dependent phagocytosis"                                    
## [21] "Cellular response to chemical stress"                                              
## [22] "Platelet activation, signaling and aggregation"                                    
## [23] "Golgi-to-ER retrograde transport"                                                  
## [24] "Leishmania infection"                                                              
## [25] "Parasitic Infection Pathways"                                                      
## [26] "RHO GTPase Effectors"                                                              
## [27] "Hemostasis"                                                                        
## [28] "Vesicle-mediated transport"                                                        
## [29] "Transport to the Golgi and subsequent modification"                                
## [30] "Intra-Golgi and retrograde Golgi-to-ER traffic"                                    
## [31] "Membrane Trafficking"                                                              
## [32] "Innate Immune System"                                                              
## [33] "Immune System"

# DEX
dex_l <- list("t0 dex up"=m_dex_t0_adj_up,"t0 dex dn"=m_dex_t0_adj_dn,
  "EOS dex up"=m_dex_eos_adj_up, "EOS dex dn"=m_dex_eos_adj_dn,
  "POD1 dex up"=m_dex_pod1_adj_up, "POD1 dex dn"=m_dex_pod1_adj_dn)

plot(euler(dex_l),quantities = TRUE)

dex_l <- list("t0 dex up"=m_dex_t0_adj_up,"t0 dex dn"=m_dex_t0_adj_dn,
  "EOS dex up"=m_dex_eos_adj_up, "EOS dex dn"=m_dex_eos_adj_dn)

plot(euler(dex_l),quantities = TRUE)

intersect(m_dex_t0_adj_up,m_dex_eos_adj_up)

## [1] "Expression and translocation of olfactory receptors"
## [2] "Olfactory Signaling Pathway"

intersect(m_dex_t0_adj_dn,m_dex_eos_adj_dn)

## [1] "PD-1 signaling"                  "Gene expression (Transcription)"
## [3] "RNA Polymerase II Transcription" "Generic Transcription Pathway"

intersect(m_dex_t0_adj_up,m_dex_eos_adj_dn)

## character(0)

intersect(m_dex_t0_adj_dn,m_dex_eos_adj_up)

##  [1] "CD22 mediated BCR regulation"                                                      
##  [2] "Classical antibody-mediated complement activation"                                 
##  [3] "Role of phospholipids in phagocytosis"                                             
##  [4] "Scavenging of heme from plasma"                                                    
##  [5] "FCGR activation"                                                                   
##  [6] "Creation of C4 and C2 activators"                                                  
##  [7] "Initial triggering of complement"                                                  
##  [8] "FCGR3A-mediated IL10 synthesis"                                                    
##  [9] "Role of LAT2/NTAL/LAB on calcium mobilization"                                     
## [10] "FCERI mediated Ca+2 mobilization"                                                  
## [11] "Antigen activates B Cell Receptor (BCR) leading to generation of second messengers"
## [12] "Regulation of actin dynamics for phagocytic cup formation"                         
## [13] "Fcgamma receptor (FCGR) dependent phagocytosis"                                    
## [14] "FCGR3A-mediated phagocytosis"                                                      
## [15] "Leishmania phagocytosis"                                                           
## [16] "Parasite infection"                                                                
## [17] "Binding and Uptake of Ligands by Scavenger Receptors"                              
## [18] "Regulation of Complement cascade"                                                  
## [19] "FCERI mediated MAPK activation"                                                    
## [20] "Complement cascade"                                                                
## [21] "Anti-inflammatory response favouring Leishmania parasite infection"                
## [22] "Leishmania parasite growth and survival"                                           
## [23] "Cell surface interactions at the vascular wall"                                    
## [24] "Signaling by the B Cell Receptor (BCR)"                                            
## [25] "FCERI mediated NF-kB activation"                                                   
## [26] "Leishmania infection"                                                              
## [27] "Parasitic Infection Pathways"                                                      
## [28] "Vesicle-mediated transport"                                                        
## [29] "Fc epsilon receptor (FCERI) signaling"                                             
## [30] "Membrane Trafficking"                                                              
## [31] "Hemostasis"                                                                        
## [32] "Innate Immune System"                                                              
## [33] "Metabolism of proteins"

dex_l <- list("EOS dex up"=m_dex_eos_adj_up, "EOS dex dn"=m_dex_eos_adj_dn,
  "POD1 dex up"=m_dex_pod1_adj_up, "POD1 dex dn"=m_dex_pod1_adj_dn)

plot(euler(dex_l),quantities = TRUE)

pdf("pw_euler_dex.pdf",width=5,height=5)
plot(euler(dex_l),quantities = TRUE)
dev.off()

## svg 
##   2

intersect(m_dex_eos_adj_up,m_dex_pod1_adj_up)

## character(0)

intersect(m_dex_eos_adj_dn,m_dex_pod1_adj_dn)

## [1] "Generic Transcription Pathway"   "RNA Polymerase II Transcription"
## [3] "Gene expression (Transcription)"

intersect(m_dex_eos_adj_up,m_dex_pod1_adj_dn)

##  [1] "CD22 mediated BCR regulation"                                                      
##  [2] "Classical antibody-mediated complement activation"                                 
##  [3] "Scavenging of heme from plasma"                                                    
##  [4] "Creation of C4 and C2 activators"                                                  
##  [5] "Role of LAT2/NTAL/LAB on calcium mobilization"                                     
##  [6] "FCGR activation"                                                                   
##  [7] "Regulation of Complement cascade"                                                  
##  [8] "Binding and Uptake of Ligands by Scavenger Receptors"                              
##  [9] "Antigen activates B Cell Receptor (BCR) leading to generation of second messengers"
## [10] "Initial triggering of complement"                                                  
## [11] "Complement cascade"                                                                
## [12] "FCGR3A-mediated phagocytosis"                                                      
## [13] "Leishmania phagocytosis"                                                           
## [14] "Parasite infection"                                                                
## [15] "Role of phospholipids in phagocytosis"                                             
## [16] "FCERI mediated Ca+2 mobilization"                                                  
## [17] "FCERI mediated MAPK activation"                                                    
## [18] "Platelet degranulation"                                                            
## [19] "FCERI mediated NF-kB activation"                                                   
## [20] "Regulation of actin dynamics for phagocytic cup formation"                         
## [21] "FCGR3A-mediated IL10 synthesis"                                                    
## [22] "Anti-inflammatory response favouring Leishmania parasite infection"                
## [23] "Leishmania parasite growth and survival"                                           
## [24] "Response to elevated platelet cytosolic Ca2+"                                      
## [25] "Cell surface interactions at the vascular wall"                                    
## [26] "Signaling by the B Cell Receptor (BCR)"                                            
## [27] "Fc epsilon receptor (FCERI) signaling"                                             
## [28] "Fcgamma receptor (FCGR) dependent phagocytosis"                                    
## [29] "Platelet activation, signaling and aggregation"                                    
## [30] "Leishmania infection"                                                              
## [31] "Parasitic Infection Pathways"                                                      
## [32] "Hemostasis"                                                                        
## [33] "RHO GTPase Effectors"                                                              
## [34] "Neutrophil degranulation"                                                          
## [35] "Vesicle-mediated transport"                                                        
## [36] "Innate Immune System"                                                              
## [37] "Membrane Trafficking"                                                              
## [38] "Cellular responses to stimuli"                                                     
## [39] "Metabolism of proteins"

intersect(m_dex_eos_adj_dn,m_dex_pod1_adj_up)

## character(0)

cross_eos <- list("EOS dex up"=m_dex_eos_adj_up, "EOS dex dn"=m_dex_eos_adj_dn,
  "EOS CRP up"=m_crp_eos_adj_up, "EOS CRP dn"=m_crp_eos_adj_dn)

plot(euler(cross_eos),quantities = TRUE)

cross_pod1 <- list("POD1 dex up"=m_dex_pod1_adj_up, "POD1 dex dn"=m_dex_pod1_adj_dn,
  "POD1 CRP up"=m_crp_pod1_adj_up, "POD1 CRP dn"=m_crp_pod1_adj_dn)

plot(euler(cross_pod1),quantities = TRUE)

intersect(m_crp_eos_adj_up, m_dex_eos_adj_dn)

## character(0)

intersect(m_crp_eos_adj_dn, m_dex_eos_adj_up)

##  [1] "FASTK family proteins regulate processing and stability of mitochondrial RNAs"                  
##  [2] "Mitochondrial RNA degradation"                                                                  
##  [3] "rRNA processing in the mitochondrion"                                                           
##  [4] "RNA Polymerase I Promoter Opening"                                                              
##  [5] "tRNA processing in the mitochondrion"                                                           
##  [6] "Activated PKN1 stimulates transcription of AR (androgen receptor) regulated genes KLK2 and KLK3"
##  [7] "Classical antibody-mediated complement activation"                                              
##  [8] "CD22 mediated BCR regulation"                                                                   
##  [9] "Replacement of protamines by nucleosomes in the male pronucleus"                                
## [10] "Creation of C4 and C2 activators"                                                               
## [11] "Scavenging of heme from plasma"                                                                 
## [12] "Initial triggering of complement"                                                               
## [13] "Binding and Uptake of Ligands by Scavenger Receptors"                                           
## [14] "FCGR activation"                                                                                
## [15] "Regulation of Complement cascade"                                                               
## [16] "Amyloid fiber formation"                                                                        
## [17] "FCERI mediated NF-kB activation"                                                                
## [18] "Complement cascade"                                                                             
## [19] "RHO GTPases activate PKNs"                                                                      
## [20] "Chromatin modifications during the maternal to zygotic transition (MZT)"                        
## [21] "Role of LAT2/NTAL/LAB on calcium mobilization"                                                  
## [22] "Platelet degranulation"                                                                         
## [23] "Response to elevated platelet cytosolic Ca2+"                                                   
## [24] "Antigen activates B Cell Receptor (BCR) leading to generation of second messengers"             
## [25] "Role of phospholipids in phagocytosis"                                                          
## [26] "FCERI mediated MAPK activation"                                                                 
## [27] "FCGR3A-mediated phagocytosis"                                                                   
## [28] "Leishmania phagocytosis"                                                                        
## [29] "Parasite infection"                                                                             
## [30] "Signaling by the B Cell Receptor (BCR)"                                                         
## [31] "FCERI mediated Ca+2 mobilization"                                                               
## [32] "Regulation of actin dynamics for phagocytic cup formation"                                      
## [33] "Metabolism of proteins"                                                                         
## [34] "Cellular responses to stimuli"                                                                  
## [35] "Fc epsilon receptor (FCERI) signaling"                                                          
## [36] "Cell surface interactions at the vascular wall"                                                 
## [37] "FCGR3A-mediated IL10 synthesis"                                                                 
## [38] "Anti-inflammatory response favouring Leishmania parasite infection"                             
## [39] "Leishmania parasite growth and survival"                                                        
## [40] "Fcgamma receptor (FCGR) dependent phagocytosis"                                                 
## [41] "Axon guidance"                                                                                  
## [42] "Platelet activation, signaling and aggregation"                                                 
## [43] "Leishmania infection"                                                                           
## [44] "Parasitic Infection Pathways"                                                                   
## [45] "RHO GTPase Effectors"                                                                           
## [46] "Hemostasis"                                                                                     
## [47] "Vesicle-mediated transport"                                                                     
## [48] "Membrane Trafficking"                                                                           
## [49] "Innate Immune System"

intersect(m_crp_pod1_adj_up, m_dex_pod1_adj_dn)

##  [1] "Interaction between L1 and Ankyrins"                                                                    
##  [2] "Formation of the beta-catenin:TCF transactivating complex"                                              
##  [3] "Antimicrobial peptides"                                                                                 
##  [4] "Transcriptional regulation of granulopoiesis"                                                           
##  [5] "HSP90 chaperone cycle for steroid hormone receptors (SHR) in the presence of ligand"                    
##  [6] "Factors involved in megakaryocyte development and platelet production"                                  
##  [7] "Platelet homeostasis"                                                                                   
##  [8] "Anti-inflammatory response favouring Leishmania parasite infection"                                     
##  [9] "Leishmania parasite growth and survival"                                                                
## [10] "Nuclear events mediated by NFE2L2"                                                                      
## [11] "VEGFA-VEGFR2 Pathway"                                                                                   
## [12] "Antigen activates B Cell Receptor (BCR) leading to generation of second messengers"                     
## [13] "Regulation of actin dynamics for phagocytic cup formation"                                              
## [14] "Binding and Uptake of Ligands by Scavenger Receptors"                                                   
## [15] "COPI-dependent Golgi-to-ER retrograde traffic"                                                          
## [16] "Golgi-to-ER retrograde transport"                                                                       
## [17] "Neutrophil degranulation"                                                                               
## [18] "FCGR3A-mediated phagocytosis"                                                                           
## [19] "Leishmania phagocytosis"                                                                                
## [20] "Parasite infection"                                                                                     
## [21] "Role of LAT2/NTAL/LAB on calcium mobilization"                                                          
## [22] "Fcgamma receptor (FCGR) dependent phagocytosis"                                                         
## [23] "Muscle contraction"                                                                                     
## [24] "FCERI mediated Ca+2 mobilization"                                                                       
## [25] "Leishmania infection"                                                                                   
## [26] "Parasitic Infection Pathways"                                                                           
## [27] "Hemostasis"                                                                                             
## [28] "Signaling by VEGF"                                                                                      
## [29] "FCGR3A-mediated IL10 synthesis"                                                                         
## [30] "Signaling by ALK fusions and activated point mutants"                                                   
## [31] "Signaling by ALK in cancer"                                                                             
## [32] "FCERI mediated MAPK activation"                                                                         
## [33] "Response to elevated platelet cytosolic Ca2+"                                                           
## [34] "Epigenetic regulation of adipogenesis genes by MLL3 and MLL4 complexes"                                 
## [35] "Epigenetic regulation of gene expression by MLL3 and MLL4 complexes"                                    
## [36] "MLL4 and MLL3 complexes regulate expression of PPARG target genes in adipogenesis and hepatic steatosis"
## [37] "Cell surface interactions at the vascular wall"                                                         
## [38] "Signaling by Interleukins"                                                                              
## [39] "Platelet degranulation"                                                                                 
## [40] "Platelet activation, signaling and aggregation"                                                         
## [41] "KEAP1-NFE2L2 pathway"                                                                                   
## [42] "Transport to the Golgi and subsequent modification"                                                     
## [43] "Transcriptional regulation by RUNX1"                                                                    
## [44] "ER to Golgi Anterograde Transport"                                                                      
## [45] "RHO GTPase Effectors"                                                                                   
## [46] "ESR-mediated signaling"                                                                                 
## [47] "TCF dependent signaling in response to WNT"                                                             
## [48] "Fc epsilon receptor (FCERI) signaling"                                                                  
## [49] "Signaling by the B Cell Receptor (BCR)"                                                                 
## [50] "MAPK family signaling cascades"                                                                         
## [51] "Vesicle-mediated transport"                                                                             
## [52] "Signaling by Rho GTPases"                                                                               
## [53] "Signaling by Rho GTPases, Miro GTPases and RHOBTB3"                                                     
## [54] "MAPK1/MAPK3 signaling"                                                                                  
## [55] "RHO GTPase cycle"                                                                                       
## [56] "RAF/MAP kinase cascade"                                                                                 
## [57] "Signaling by WNT"                                                                                       
## [58] "Cellular response to chemical stress"                                                                   
## [59] "Membrane Trafficking"                                                                                   
## [60] "Signal Transduction"                                                                                    
## [61] "Innate Immune System"                                                                                   
## [62] "Intra-Golgi and retrograde Golgi-to-ER traffic"                                                         
## [63] "Diseases of signal transduction by growth factor receptors and second messengers"                       
## [64] "Immune System"                                                                                          
## [65] "Cytokine Signaling in Immune system"

intersect(m_crp_pod1_adj_dn, m_dex_pod1_adj_up)

##  [1] "Formation of a pool of free 40S subunits"                                    
##  [2] "Peptide chain elongation"                                                    
##  [3] "Eukaryotic Translation Elongation"                                           
##  [4] "Selenocysteine synthesis"                                                    
##  [5] "Viral mRNA Translation"                                                      
##  [6] "Eukaryotic Translation Termination"                                          
##  [7] "L13a-mediated translational silencing of Ceruloplasmin expression"           
##  [8] "Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)"
##  [9] "GTP hydrolysis and joining of the 60S ribosomal subunit"                     
## [10] "Cap-dependent Translation Initiation"                                        
## [11] "Eukaryotic Translation Initiation"                                           
## [12] "Response of EIF2AK4 (GCN2) to amino acid deficiency"                         
## [13] "Selenoamino acid metabolism"                                                 
## [14] "Major pathway of rRNA processing in the nucleolus and cytosol"               
## [15] "rRNA processing in the nucleus and cytosol"                                  
## [16] "Influenza Viral RNA Transcription and Replication"                           
## [17] "rRNA processing"                                                             
## [18] "Influenza Infection"

Multi-contrast enrichment analysis.

l1 <- list("crp_t0_adj"=crp_t0_adj,"crp_eos_adj"=crp_eos_adj,
  "crp_pod1_adj"=crp_pod1_adj,"dex_t0_adj"=dex_t0_adj,
  "dex_eos_adj"=dex_eos_adj,"dex_pod1_adj"=dex_pod1_adj)

m1 <- mitch_import(x=l1, DEtype="deseq2", geneTable=gt )

## Note: Mean no. genes in input = 21771.6666666667

## Note: no. genes in output = 21032

## Note: estimated proportion of input genes in output = 0.966

mm1 <- mitch_calc(x=m1,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be 
##             statistically significant.

top <- head(subset (mm1$enrichment_result,p.adjustMANOVA<0.01),50)
top <- top[,c(1,4:9)]
rownames(top) <- top[,1]
top[,1] = NULL

colfunc <- colorRampPalette(c("blue", "white", "red"))

heatmap.2(as.matrix(top),trace="none",col=colfunc(25),scale="none",
    margins = c(6,25), cexRow=0.6, cexCol=0.8 )

as.matrix(top) |> kbl(caption="Top REACTOMEs in multi enrichment analysis") |> kable_paper("hover", full_width = F)

Top REACTOMEs in multi enrichment analysis

	s.crp_t0_adj	s.crp_eos_adj	s.crp_pod1_adj	s.dex_t0_adj	s.dex_eos_adj	s.dex_pod1_adj
Regulation of NFE2L2 gene expression	0.5891124	0.6426703	0.5937738	-0.8527635	-0.1618626	0.0422256
Protein repair	-0.5129839	-0.4712578	0.3864422	0.4543739	0.7444117	-0.6464060
G2/M DNA replication checkpoint	-0.1564940	-0.5453084	0.6956294	-0.4163314	0.6024920	-0.6742854
Interleukin-21 signaling	0.2427553	0.6305634	0.3235874	-0.7074738	-0.5108849	-0.6565983
Response to metal ions	0.2238815	-0.4391547	0.7772440	-0.1266210	0.5004439	-0.6564571
CD163 mediating an anti-inflammatory response	-0.1675466	0.0306198	0.8753092	0.0381826	0.7841990	0.0577911
Defective binding of VWF variant to GPIb:IX:V	0.4129453	-0.7073667	0.3276835	0.2818947	0.7251153	-0.1213583
Enhanced binding of GP1BA variant to VWF multimer:collagen	0.4129453	-0.7073667	0.3276835	0.2818947	0.7251153	-0.1213583
Formation of a pool of free 40S subunits	-0.2566317	-0.8482730	-0.6834238	0.1132391	0.0326057	0.2670015
Peptide chain elongation	-0.2300711	-0.8496292	-0.6805712	0.1099096	0.0032230	0.2732460
Eukaryotic Translation Elongation	-0.2150399	-0.8408216	-0.6686039	0.1031643	-0.0006769	0.2638263
Tandem pore domain potassium channels	-0.2743045	0.4669520	0.3646264	-0.4240928	-0.6839112	-0.4323679
Viral mRNA Translation	-0.2357016	-0.8380356	-0.6547992	0.1134131	0.0177394	0.2422804
L13a-mediated translational silencing of Ceruloplasmin expression	-0.2894286	-0.8311020	-0.6395205	0.1317057	0.0702282	0.2271084
MET activates PI3K/AKT signaling	-0.4461407	0.5910211	0.4899700	0.2374946	0.4361725	-0.4579160
Type I hemidesmosome assembly	0.1838732	0.3568422	0.5685883	-0.5944873	-0.2748288	-0.5740939
GTP hydrolysis and joining of the 60S ribosomal subunit	-0.2881499	-0.8265123	-0.6271945	0.1368060	0.0694206	0.2223427
Selenocysteine synthesis	-0.2285296	-0.8105824	-0.6634070	0.0895457	-0.0035343	0.2575803
SARS-CoV-1 modulates host translation machinery	-0.1977758	-0.8159914	-0.6547173	0.1223752	0.0174822	0.2659845
Formation of the ternary complex, and subsequently, the 43S complex	-0.2805405	-0.8092074	-0.6417300	0.1415408	0.0843424	0.2150059
Cap-dependent Translation Initiation	-0.2791588	-0.8205328	-0.6233260	0.1298291	0.0611261	0.2299879
Eukaryotic Translation Initiation	-0.2791588	-0.8205328	-0.6233260	0.1298291	0.0611261	0.2299879
Eukaryotic Translation Termination	-0.2201365	-0.8159854	-0.6516251	0.0855229	0.0029518	0.2416297
POLB-Dependent Long Patch Base Excision Repair	0.1600076	-0.2593584	-0.5704790	-0.6590563	-0.5523806	0.1608162
Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	-0.2287798	-0.8079039	-0.6339731	0.0859727	0.0370164	0.2443878
Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	-0.3254669	-0.7927085	-0.5959211	0.1553256	0.1335155	0.2064179
Translation initiation complex formation	-0.3192886	-0.7895309	-0.5905045	0.1471247	0.1325467	0.1938936
Ribosomal scanning and start codon recognition	-0.3196371	-0.7878260	-0.5767518	0.1538456	0.1338274	0.1999602
SRP-dependent cotranslational protein targeting to membrane	-0.3137107	-0.8098165	-0.5609328	0.0984679	0.1043269	0.0969541
Replacement of protamines by nucleosomes in the male pronucleus	-0.2815335	-0.6127973	0.2507929	0.2857358	0.6285284	-0.3005867
FASTK family proteins regulate processing and stability of mitochondrial RNAs	-0.0945004	-0.7225026	-0.0366665	0.1400311	0.6907979	0.1462929
Response of EIF2AK4 (GCN2) to amino acid deficiency	-0.2305137	-0.7689801	-0.5831945	0.1372976	0.0329223	0.2135177
Post-transcriptional silencing by small RNAs	-0.2110888	0.7144488	0.3229013	-0.2452251	-0.3767420	-0.4195889
CD22 mediated BCR regulation	0.1548753	-0.5511632	0.2320482	-0.4078765	0.5203898	-0.4512348
Mitochondrial translation initiation	-0.1122264	-0.8032725	-0.5660746	-0.0899744	0.1013604	0.0875858
Regulation of NPAS4 gene expression	-0.1496123	0.6113583	0.2834871	-0.3270452	-0.4092228	-0.4968149
Formation of ATP by chemiosmotic coupling	-0.3101704	-0.8499857	-0.2985342	-0.0290881	0.2919998	-0.0351371
Mitochondrial translation elongation	-0.1010261	-0.7899925	-0.5572130	-0.0970023	0.1003173	0.1107514
Mitochondrial translation termination	-0.1051348	-0.7796751	-0.5482773	-0.0807076	0.1004478	0.0999671
Mitochondrial translation	-0.1258677	-0.7725011	-0.5479328	-0.0651748	0.0943879	0.1012232
Selenoamino acid metabolism	-0.2452475	-0.7159099	-0.5521770	0.0807682	0.0175673	0.2239706
Complex III assembly	-0.2200237	-0.7576939	-0.4752228	-0.0533829	0.0726004	0.2708053
Cohesin Loading onto Chromatin	-0.4444392	0.4621825	0.3944725	-0.2755304	-0.0609076	-0.5317477
RNA Polymerase I Promoter Opening	-0.1883976	-0.6725896	0.2127724	0.1930722	0.5103190	-0.3116541
Regulation of CDH11 mRNA translation by microRNAs	-0.1158557	0.6330979	0.2043974	-0.3220486	-0.4499857	-0.4008514
Regulation of NPAS4 mRNA translation	-0.1158557	0.6330979	0.2043974	-0.3220486	-0.4499857	-0.4008514
Chk1/Chk2(Cds1) mediated inactivation of Cyclin B:Cdk1 complex	-0.3307520	-0.4990320	0.3344044	-0.0156598	0.4715184	-0.4493627
Mitochondrial RNA degradation	-0.1194707	-0.6793907	-0.0976037	0.1554853	0.6061808	0.0946941
Regulation of IFNA/IFNB signaling	0.0028386	0.3153346	0.4433714	-0.2962575	-0.2029099	-0.6789248
SARS-CoV-2 modulates host translation machinery	-0.0688769	-0.7262293	-0.5494662	0.0380609	-0.0123725	0.2127699

mitch_report(res=mm1,outfile="multireactome_all_mitchreport.html",overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/multireactome_all_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

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## 6/36 [metrics]                   
## 7/36                             
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## 9/36                             
## 10/36 [contourplot]

## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]    
## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]

## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]
## 30/36                             
## 31/36 [detailed_geneset_reports2d]

## 32/36                             
## 33/36 [network]                   
## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e5619e0a7.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

This might work better if we work on each timepoint separately.

l1 <- list("crp_t0_adj"=crp_t0_adj, "dex_t0_adj"=dex_t0_adj)
m1 <- mitch_import(x=l1, DEtype="deseq2", geneTable=gt )

## Note: Mean no. genes in input = 21935

## Note: no. genes in output = 21870

## Note: estimated proportion of input genes in output = 0.997

mm1 <- mitch_calc(x=m1,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be 
##             statistically significant.

top <- head(subset (mm1$enrichment_result,p.adjustMANOVA<0.01),50)
top <- top[,c(1,4:5)]
rownames(top) <- top[,1]
top[,1] = NULL
heatmap.2(as.matrix(top),trace="none",col=colfunc(25),scale="none", margins = c(6,25), cexRow=0.6, cexCol=0.8 )

as.matrix(top) |> kbl(caption="Top REACTOMEs in multi enrichment analysis at t0") |> kable_paper("hover", full_width = F)

Top REACTOMEs in multi enrichment analysis at t0

	s.crp_t0_adj	s.dex_t0_adj
Regulation of NFE2L2 gene expression	0.5831580	-0.8540733
NR1H2 & NR1H3 regulate gene expression to control bile acid homeostasis	-0.0547631	-0.7570978
Interleukin-21 signaling	0.2372312	-0.7099452
Disorders of Developmental Biology	0.1587519	-0.6191860
Disorders of Nervous System Development	0.1587519	-0.6191860
Loss of function of MECP2 in Rett syndrome	0.1587519	-0.6191860
Pervasive developmental disorders	0.1587519	-0.6191860
Eicosanoids	0.0688066	0.6353376
NR1H2 & NR1H3 regulate gene expression linked to lipogenesis	-0.1419586	-0.5977152
NR1H3 & NR1H2 regulate gene expression linked to cholesterol transport and efflux	-0.0718215	-0.5723853
TP53 Regulates Transcription of Genes Involved in G2 Cell Cycle Arrest	0.2702016	-0.4913051
Formation of annular gap junctions	-0.3688564	-0.4207594
Processing and activation of SUMO	-0.5306130	-0.1210522
Processive synthesis on the C-strand of the telomere	0.0634272	-0.5354085
Removal of the Flap Intermediate from the C-strand	-0.0132786	-0.5311991
Cohesin Loading onto Chromatin	-0.4495151	-0.2809058
NR1H2 and NR1H3-mediated signaling	-0.1034406	-0.5174201
ATF6 (ATF6-alpha) activates chaperones	-0.5136487	-0.0869171
SARS-CoV-2 modulates autophagy	-0.3592571	-0.3609622
Antigen Presentation: Folding, assembly and peptide loading of class I MHC	-0.4649512	-0.2040842
HDMs demethylate histones	0.0890679	-0.4926954
HSF1-dependent transactivation	0.2537515	-0.4033974
Regulation of TP53 Activity through Acetylation	0.0969815	-0.4636314
ER Quality Control Compartment (ERQC)	-0.4699594	0.0296821
Mitotic Telophase/Cytokinesis	-0.2064855	-0.4203512
Signaling by ALK	0.1830312	-0.4293311
RORA activates gene expression	-0.0246964	-0.4571511
Calnexin/calreticulin cycle	-0.4506113	-0.0802227
N-glycan trimming in the ER and Calnexin/Calreticulin cycle	-0.4448310	-0.0742909
PD-1 signaling	0.1973001	-0.3916635
CD22 mediated BCR regulation	0.1635475	-0.4045797
Expression and translocation of olfactory receptors	0.0549511	0.4240976
Pre-NOTCH Processing in Golgi	-0.0795706	-0.4152429
SUMOylation of DNA replication proteins	-0.0718814	-0.4154481
DNA strand elongation	0.1817846	-0.3672555
Glycosphingolipid catabolism	-0.3664959	0.1802886
G0 and Early G1	0.0764021	-0.3981155
Transport of Ribonucleoproteins into the Host Nucleus	-0.1829122	-0.3576049
Nuclear Pore Complex (NPC) Disassembly	-0.1407438	-0.3716935
Regulation of MECP2 expression and activity	-0.0122216	-0.3885874
Nuclear import of Rev protein	-0.1564820	-0.3549185
Vpr-mediated nuclear import of PICs	-0.1535942	-0.3535527
Classical antibody-mediated complement activation	0.0236265	-0.3823630
Signaling by cytosolic FGFR1 fusion mutants	-0.3325350	-0.1896750
Golgi Associated Vesicle Biogenesis	-0.3805880	-0.0026179
Olfactory Signaling Pathway	0.0329572	0.3781979
SUMOylation of SUMOylation proteins	-0.1350218	-0.3525362
Role of phospholipids in phagocytosis	0.0496232	-0.3709341
Rev-mediated nuclear export of HIV RNA	-0.1003697	-0.3601753
Scavenging of heme from plasma	0.0538021	-0.3693870

mitch_report(res=mm1,outfile="multireactome_t0_mitchreport.html",overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/multireactome_t0_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 3/36                             
## 4/36 [peek]                      
## 5/36                             
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## 7/36                             
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## 9/36                             
## 10/36 [contourplot]

## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]

## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]
## 30/36                             
## 31/36 [detailed_geneset_reports2d]

## 32/36                             
## 33/36 [network]                   
## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e396ef64c.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

l1 <- list("crp_eos_adj"=crp_eos_adj, "dex_eos_adj"=dex_eos_adj)
m1 <- mitch_import(x=l1, DEtype="deseq2", geneTable=gt )

## Note: Mean no. genes in input = 22067

## Note: no. genes in output = 21999

## Note: estimated proportion of input genes in output = 0.997

mm1 <- mitch_calc(x=m1,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be 
##             statistically significant.

top <- head(subset (mm1$enrichment_result,p.adjustMANOVA<0.01),50)
top <- top[,c(1,4:5)]
rownames(top) <- top[,1]
top[,1] = NULL
heatmap.2(as.matrix(top),trace="none",col=colfunc(25),scale="none", margins = c(6,25), cexRow=0.6, cexCol=0.8 )

as.matrix(top) |> kbl(caption="Top REACTOMEs in multi enrichment analysis at EOS") |> kable_paper("hover", full_width = F)

Top REACTOMEs in multi enrichment analysis at EOS

	s.crp_eos_adj	s.dex_eos_adj
FASTK family proteins regulate processing and stability of mitochondrial RNAs	-0.7269863	0.6869930
Modulation by Mtb of host immune system	-0.8262745	0.4784077
Mitochondrial RNA degradation	-0.6840266	0.6015728
Defective binding of VWF variant to GPIb:IX:V	-0.5438601	0.7242764
Enhanced binding of GP1BA variant to VWF multimer:collagen	-0.5438601	0.7242764
Formation of ATP by chemiosmotic coupling	-0.8530097	0.2819601
tRNA processing in the mitochondrion	-0.6356997	0.5660978
RNA Polymerase I Promoter Opening	-0.6758712	0.5063153
Peptide chain elongation	-0.8425500	-0.0139957
Formation of a pool of free 40S subunits	-0.8424586	0.0159468
Eukaryotic Translation Elongation	-0.8344461	-0.0176227
Viral mRNA Translation	-0.8310738	0.0004979
L13a-mediated translational silencing of Ceruloplasmin expression	-0.8264234	0.0539615
GTP hydrolysis and joining of the 60S ribosomal subunit	-0.8220128	0.0532012
Formation of xylulose-5-phosphate	-0.6024007	-0.5603892
SARS-CoV-1 modulates host translation machinery	-0.8190467	0.0051602
Cap-dependent Translation Initiation	-0.8166167	0.0453493
Eukaryotic Translation Initiation	-0.8166167	0.0453493
Formation of the ternary complex, and subsequently, the 43S complex	-0.8125909	0.0726691
Interleukin-21 signaling	0.6277500	-0.5174372
Mitochondrial translation initiation	-0.8069794	0.0908769
rRNA processing in the mitochondrion	-0.6804399	0.4416875
SRP-dependent cotranslational protein targeting to membrane	-0.8054049	0.0880864
Eukaryotic Translation Termination	-0.8098801	-0.0138223
Packaging Of Telomere Ends	-0.6982343	0.4097781
Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	-0.7962038	0.1222842
Selenocysteine synthesis	-0.8045731	-0.0205186
Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	-0.8021981	0.0201654
Translation initiation complex formation	-0.7930814	0.1213144
Ribosomal scanning and start codon recognition	-0.7914203	0.1226172
Mitochondrial translation elongation	-0.7937134	0.0898941
Mitochondrial translation termination	-0.7834599	0.0900046
Mitochondrial translation	-0.7762502	0.0838403
Replacement of protamines by nucleosomes in the male pronucleus	-0.5183019	0.5802644
Complex III assembly	-0.7620645	0.0632429
Response of EIF2AK4 (GCN2) to amino acid deficiency	-0.7641153	0.0164638
RUNX1 regulates transcription of genes involved in BCR signaling	0.3380318	0.6846118
CD163 mediating an anti-inflammatory response	0.0320247	0.7518468
Activated PKN1 stimulates transcription of AR (androgen receptor) regulated genes KLK2 and KLK3	-0.5815119	0.4711657
CD22 mediated BCR regulation	-0.5349660	0.5129462
Regulation of NPAS4 gene expression	0.6083153	-0.4176410
Translation	-0.7315663	0.0743318
SIRT1 negatively regulates rRNA expression	-0.6151204	0.4028282
Cleavage of the damaged purine	-0.6611912	0.3212615
Depurination	-0.6611912	0.3212615
Recognition and association of DNA glycosylase with site containing an affected purine	-0.6611912	0.3212615
SARS-CoV-2 modulates host translation machinery	-0.7302310	-0.0243113
Cristae formation	-0.7043392	0.1673192
Mitochondrial calcium ion transport	-0.6998598	0.1601799
TGFBR3 expression	0.5804677	-0.4152464

mitch_report(res=mm1,outfile="multireactome_eos_mitchreport.html",overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/multireactome_eos_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 4/36 [peek]                      
## 5/36                             
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## 7/36                             
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## 9/36                             
## 10/36 [contourplot]

## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]

## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]
## 30/36                             
## 31/36 [detailed_geneset_reports2d]

## 32/36                             
## 33/36 [network]                   
## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e5aef7e7d.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

mitch_plots(res=mm1,outfile="multireactome_eos_mitchplots.pdf")

## svg 
##   2

l1 <- list("crp_pod1_adj"=crp_pod1_adj, "dex_pod1_adj"=dex_pod1_adj)
m1 <- mitch_import(x=l1, DEtype="deseq2", geneTable=gt )

## Note: Mean no. genes in input = 21313

## Note: no. genes in output = 21253

## Note: estimated proportion of input genes in output = 0.997

mm1 <- mitch_calc(x=m1,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be 
##             statistically significant.

top <- head(subset (mm1$enrichment_result,p.adjustMANOVA<0.01),50)
top <- top[,c(1,4:5)]
rownames(top) <- top[,1]
top[,1] = NULL
heatmap.2(as.matrix(top),trace="none",col=colfunc(25),scale="none", margins = c(6,25), cexRow=0.6, cexCol=0.8 )

as.matrix(top) |> kbl(caption="Top REACTOMEs in multi enrichment analysis at POD1") |> kable_paper("hover", full_width = F)

Top REACTOMEs in multi enrichment analysis at POD1

	s.crp_pod1_adj	s.dex_pod1_adj
Insulin-like Growth Factor-2 mRNA Binding Proteins (IGF2BPs/IMPs/VICKZs) bind RNA	0.8139973	-0.6102195
CD163 mediating an anti-inflammatory response	0.8726171	0.0578724
Butyrophilin (BTN) family interactions	-0.5751165	0.6249306
Regulation of IFNA/IFNB signaling	0.4407200	-0.6790484
Activation of caspases through apoptosome-mediated cleavage	0.1436752	-0.7807534
Inhibition of Signaling by Overexpressed EGFR	0.7530497	0.2023532
Signaling by Overexpressed Wild-Type EGFR in Cancer	0.7530497	0.2023532
Establishment of Sister Chromatid Cohesion	0.3437444	-0.6895345
Formation of a pool of free 40S subunits	-0.6858006	0.2577601
Peptide chain elongation	-0.6830735	0.2626796
Mitotic Telophase/Cytokinesis	0.4479429	-0.5647834
Eukaryotic Translation Elongation	-0.6712269	0.2539230
Selenocysteine synthesis	-0.6661198	0.2476449
SARS-CoV-1 modulates host translation machinery	-0.6564809	0.2660210
Viral mRNA Translation	-0.6576209	0.2320576
Eukaryotic Translation Termination	-0.6545162	0.2318601
EGFR interacts with phospholipase C-gamma	0.6545238	0.2238434
Platelet sensitization by LDL	0.4364788	-0.5274639
Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	-0.6370419	0.2347927
L13a-mediated translational silencing of Ceruloplasmin expression	-0.6423248	0.2190624
Formation of the ternary complex, and subsequently, the 43S complex	-0.6435538	0.2150297
GTP hydrolysis and joining of the 60S ribosomal subunit	-0.6301576	0.2144120
Cap-dependent Translation Initiation	-0.6262726	0.2224529
Eukaryotic Translation Initiation	-0.6262726	0.2224529
rRNA modification in the mitochondrion	-0.6391975	-0.0022594
Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	-0.5977739	0.2064351
Translation initiation complex formation	-0.5923778	0.1939137
Response of EIF2AK4 (GCN2) to amino acid deficiency	-0.5868378	0.2047965
Interaction between L1 and Ankyrins	0.4903334	-0.3804806
RHO GTPases activate IQGAPs	0.5020878	-0.3513473
Ribosomal scanning and start codon recognition	-0.5786889	0.1999805
Synthesis of Leukotrienes (LT) and Eoxins (EX)	0.5782214	-0.1928116
Regulation of RUNX1 Expression and Activity	0.3376135	-0.4946864
Selenoamino acid metabolism	-0.5559006	0.2163012
SARS-CoV-2 modulates host translation machinery	-0.5516691	0.2127496
Mitochondrial translation initiation	-0.5682570	0.0875837
SRP-dependent cotranslational protein targeting to membrane	-0.5647526	0.0901165
Mitochondrial translation elongation	-0.5594355	0.1107572
GAB1 signalosome	0.5559920	-0.1248848
Major pathway of rRNA processing in the nucleolus and cytosol	-0.5238381	0.2202629
Nonsense Mediated Decay (NMD) enhanced by the Exon Junction Complex (EJC)	-0.5420803	0.1648130
Nonsense-Mediated Decay (NMD)	-0.5420803	0.1648130
rRNA processing in the nucleus and cytosol	-0.5209606	0.2191924
Mitochondrial translation termination	-0.5505038	0.0999690
Mitochondrial translation	-0.5501637	0.1012224
Influenza Viral RNA Transcription and Replication	-0.5186532	0.1914730
G0 and Early G1	0.3095644	-0.4542019
Complex III assembly	-0.4776956	0.2708309
rRNA processing	-0.4879166	0.2064429
CD22 mediated BCR regulation	0.2367588	-0.4582831

mitch_report(res=mm1,outfile="multireactome_pod1_mitchreport.html",overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/multireactome_pod1_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

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## 6/36 [metrics]                   
## 7/36                             
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## 10/36 [contourplot]

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## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
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## 17/36                             
## 18/36 [echart1d]                  
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## 20/36                             
## 21/36 [heatmap]

## 22/36                             
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## 24/36                             
## 25/36 [results_table]             
## 26/36                             
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## 28/36                             
## 29/36 [detailed_geneset_reports1d]
## 30/36                             
## 31/36 [detailed_geneset_reports2d]

## 32/36                             
## 33/36 [network]                   
## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e2d2c4794.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

mitch_plots(res=mm1,outfile="multireactome_pod1_mitchplots.pdf")

## svg 
##   2

Individual contrast analysis stratified

• crp_t0_a_adj
• crp_t0_b_adj
• crp_eos_a_adj
• crp_eos_b_adj
• crp_pod1_a_adj
• crp_pod1_b_adj
• dex_crplo_t0_adj
• dex_crphi_t0_adj
• dex_crplo_eos_adj
• dex_crphi_eos_adj
• dex_crplo_pod1_adj
• dex_crphi_pod1_adj

de <- crp_t0_a_adj
myname <- "crp_t0_a_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21935

## Note: no. genes in output = 21870

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

crp_t0_a_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
943	Modulation by Mtb of host immune system	7	0.0001742	-0.8191857	0.0009456
1125	Peptide chain elongation	87	0.0000000	-0.8159548	0.0000000
879	Maturation of spike protein_9683686	5	0.0017664	-0.8074182	0.0071510
1862	Viral mRNA Translation	87	0.0000000	-0.8061728	0.0000000
547	Formation of ATP by chemiosmotic coupling	20	0.0000000	-0.7990755	0.0000000
492	Eukaryotic Translation Elongation	92	0.0000000	-0.7971247	0.0000000
556	Formation of a pool of free 40S subunits	99	0.0000000	-0.7868622	0.0000000
1452	SARS-CoV-1 modulates host translation machinery	36	0.0000000	-0.7859607	0.0000000
494	Eukaryotic Translation Termination	91	0.0000000	-0.7823319	0.0000000
659	Glycosphingolipid transport	7	0.0004072	-0.7715383	0.0020379
1512	Selenocysteine synthesis	91	0.0000000	-0.7670404	0.0000000
1037	Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	93	0.0000000	-0.7653665	0.0000000
1485	SRP-dependent cotranslational protein targeting to membrane	110	0.0000000	-0.7565157	0.0000000
812	L13a-mediated translational silencing of Ceruloplasmin expression	109	0.0000000	-0.7511549	0.0000000
557	Formation of annular gap junctions	10	0.0000428	-0.7471089	0.0002571
616	GTP hydrolysis and joining of the 60S ribosomal subunit	110	0.0000000	-0.7368608	0.0000000
1141	Phosphate bond hydrolysis by NUDT proteins	7	0.0009235	-0.7229893	0.0040817
218	Cap-dependent Translation Initiation	117	0.0000000	-0.7219992	0.0000000
493	Eukaryotic Translation Initiation	117	0.0000000	-0.7219992	0.0000000
1431	Response of EIF2AK4 (GCN2) to amino acid deficiency	99	0.0000000	-0.7211915	0.0000000
569	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0000000	-0.7012318	0.0000000
72	Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	59	0.0000000	-0.6829076	0.0000000
1799	Translation initiation complex formation	58	0.0000000	-0.6788481	0.0000000
1443	Ribosomal scanning and start codon recognition	58	0.0000000	-0.6711649	0.0000000
577	Fructose metabolism	7	0.0022264	-0.6674355	0.0087917
1511	Selenoamino acid metabolism	114	0.0000000	-0.6654651	0.0000000
1185	Prevention of phagosomal-lysosomal fusion	9	0.0005887	-0.6614875	0.0027806
1856	VLDLR internalisation and degradation	15	0.0000095	-0.6602151	0.0000627
994	Nef Mediated CD4 Down-regulation	9	0.0006764	-0.6542193	0.0031559
1114	PTK6 Regulates RTKs and Their Effectors AKT1 and DOK1	9	0.0007766	-0.6469105	0.0035213

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/crp_t0_a_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 9/36                             
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## 13/36                             
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## 15/36                             
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## 17/36                             
## 18/36 [echart1d]                  
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## 20/36                             
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## 22/36                             
## 23/36 [effectsize]                
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## 29/36 [detailed_geneset_reports1d]

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## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e2125aeb9.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- crp_t0_b_adj
myname <- "crp_t0_b_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21935

## Note: no. genes in output = 21870

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

crp_t0_b_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
1674	Synthesis of PIPs at the early endosome membrane	16	3.00e-05	-0.6025613	0.0082640
180	CD22 mediated BCR regulation	59	3.60e-05	0.3109308	0.0082640
720	ISG15 antiviral mechanism	72	2.29e-05	-0.2885573	0.0082640
1508	Scavenging of heme from plasma	71	4.87e-05	0.2787239	0.0085318
109	Antiviral mechanism by IFN-stimulated genes	140	4.25e-05	-0.2003524	0.0082640
761	Interferon Signaling	240	3.05e-05	-0.1562348	0.0082640
233	Cell Cycle Checkpoints	246	4.29e-05	-0.1514389	0.0082640
631	Gene expression (Transcription)	1404	0.00e+00	-0.1127803	0.0000000
1273	RNA Polymerase II Transcription	1197	0.00e+00	-0.1119677	0.0000001
633	Generic Transcription Pathway	1079	0.00e+00	-0.1090706	0.0000009
1170	Post-translational protein modification	1245	3.72e-05	-0.0694851	0.0082640

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/crp_t0_b_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 4/36 [peek]                      
## 5/36                             
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## 7/36                             
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## 9/36                             
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## 17/36                             
## 18/36 [echart1d]                  
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## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e7a45e1b7.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- crp_eos_a_adj
myname <- "crp_eos_a_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 22067

## Note: no. genes in output = 21999

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

crp_eos_a_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
550	Formation of ATP by chemiosmotic coupling	20	0.0000000	-0.8137677	0.0000000
873	Malate-aspartate shuttle	8	0.0004343	-0.7182484	0.0036798
1213	Purine ribonucleoside monophosphate biosynthesis	9	0.0003046	-0.6950836	0.0026736
811	Ketone body metabolism	8	0.0007268	-0.6898618	0.0057788
933	Mitochondrial translation elongation	90	0.0000000	-0.6894691	0.0000000
1127	Peptide chain elongation	88	0.0000000	-0.6817705	0.0000000
934	Mitochondrial translation initiation	90	0.0000000	-0.6774710	0.0000000
1867	Viral mRNA Translation	88	0.0000000	-0.6691149	0.0000000
310	Cristae formation	33	0.0000000	-0.6654665	0.0000000
495	Eukaryotic Translation Elongation	93	0.0000000	-0.6645020	0.0000000
291	Complex III assembly	23	0.0000000	-0.6616507	0.0000009
935	Mitochondrial translation termination	90	0.0000000	-0.6604095	0.0000000
497	Eukaryotic Translation Termination	92	0.0000000	-0.6569639	0.0000000
1487	SRP-dependent cotranslational protein targeting to membrane	111	0.0000000	-0.6547855	0.0000000
559	Formation of a pool of free 40S subunits	100	0.0000000	-0.6511777	0.0000000
1514	Selenocysteine synthesis	92	0.0000000	-0.6491215	0.0000000
1454	SARS-CoV-1 modulates host translation machinery	36	0.0000000	-0.6478573	0.0000000
1039	Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	94	0.0000000	-0.6441597	0.0000000
932	Mitochondrial translation	96	0.0000000	-0.6410081	0.0000000
930	Mitochondrial protein import	63	0.0000000	-0.6387254	0.0000000
1055	Nucleotide biosynthesis	12	0.0001578	-0.6298495	0.0014944
815	L13a-mediated translational silencing of Ceruloplasmin expression	110	0.0000000	-0.6233883	0.0000000
619	GTP hydrolysis and joining of the 60S ribosomal subunit	111	0.0000000	-0.6202016	0.0000000
1433	Response of EIF2AK4 (GCN2) to amino acid deficiency	100	0.0000000	-0.6197982	0.0000000
282	Cohesin Loading onto Chromatin	10	0.0007310	0.6167720	0.0057881
220	Cap-dependent Translation Initiation	118	0.0000000	-0.6142431	0.0000000
496	Eukaryotic Translation Initiation	118	0.0000000	-0.6142431	0.0000000
1802	Translation	293	0.0000000	-0.6010691	0.0000000
1460	SARS-CoV-2 modulates host translation machinery	49	0.0000000	-0.5956896	0.0000000
1924	rRNA processing in the nucleus and cytosol	189	0.0000000	-0.5922801	0.0000000

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/crp_eos_a_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e64e5d7a0.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- crp_eos_b_adj
myname <- "crp_eos_b_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 22067

## Note: no. genes in output = 21999

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

crp_eos_b_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
1127	Peptide chain elongation	88	0.0000000	-0.8467468	0.0000000
559	Formation of a pool of free 40S subunits	100	0.0000000	-0.8436038	0.0000000
495	Eukaryotic Translation Elongation	93	0.0000000	-0.8382493	0.0000000
1867	Viral mRNA Translation	88	0.0000000	-0.8310977	0.0000000
1454	SARS-CoV-1 modulates host translation machinery	36	0.0000000	-0.8200737	0.0000000
1514	Selenocysteine synthesis	92	0.0000000	-0.8080453	0.0000000
815	L13a-mediated translational silencing of Ceruloplasmin expression	110	0.0000000	-0.8017335	0.0000000
220	Cap-dependent Translation Initiation	118	0.0000000	-0.8001803	0.0000000
496	Eukaryotic Translation Initiation	118	0.0000000	-0.8001803	0.0000000
619	GTP hydrolysis and joining of the 60S ribosomal subunit	111	0.0000000	-0.7993446	0.0000000
497	Eukaryotic Translation Termination	92	0.0000000	-0.7940136	0.0000000
572	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0000000	-0.7819123	0.0000000
1143	Phosphate bond hydrolysis by NUDT proteins	7	0.0003965	-0.7730733	0.0032736
1039	Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	94	0.0000000	-0.7669569	0.0000000
1433	Response of EIF2AK4 (GCN2) to amino acid deficiency	100	0.0000000	-0.7547504	0.0000000
1487	SRP-dependent cotranslational protein targeting to membrane	111	0.0000000	-0.7527980	0.0000000
73	Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	59	0.0000000	-0.7359996	0.0000000
360	Defective GALNT3 causes HFTC	9	0.0001377	0.7337275	0.0013239
1445	Ribosomal scanning and start codon recognition	58	0.0000000	-0.7322003	0.0000000
1803	Translation initiation complex formation	58	0.0000000	-0.7315119	0.0000000
550	Formation of ATP by chemiosmotic coupling	20	0.0000000	-0.7152418	0.0000005
1363	Regulation of NFE2L2 gene expression	8	0.0004992	0.7106657	0.0039527
934	Mitochondrial translation initiation	90	0.0000000	-0.6964576	0.0000000
1513	Selenoamino acid metabolism	115	0.0000000	-0.6956466	0.0000000
1460	SARS-CoV-2 modulates host translation machinery	49	0.0000000	-0.6889052	0.0000000
935	Mitochondrial translation termination	90	0.0000000	-0.6820556	0.0000000
933	Mitochondrial translation elongation	90	0.0000000	-0.6802258	0.0000000
1298	RUNX1 and FOXP3 control the development of regulatory T lymphocytes (Tregs)	9	0.0004433	0.6761356	0.0035684
1193	Processing of SMDT1	15	0.0000065	-0.6723314	0.0000866
932	Mitochondrial translation	96	0.0000000	-0.6716403	0.0000000

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/crp_eos_b_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
## 2/36 [checklibraries]            
## 3/36                             
## 4/36 [peek]                      
## 5/36                             
## 6/36 [metrics]                   
## 7/36                             
## 8/36 [scatterplot]

## 9/36                             
## 10/36 [contourplot]               
## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e1cc856e0.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- crp_pod1_a_adj
myname <- "crp_pod1_a_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21313

## Note: no. genes in output = 21253

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

crp_pod1_a_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
854	MET activates PI3K/AKT signaling	5	0.0013897	0.8254518	0.0087816
178	CD163 mediating an anti-inflammatory response	8	0.0000618	0.8177689	0.0006978
962	NFE2L2 regulates pentose phosphate pathway genes	8	0.0001501	0.7738762	0.0013730
278	Cohesin Loading onto Chromatin	10	0.0000309	0.7607683	0.0004197
484	Establishment of Sister Chromatid Cohesion	11	0.0000933	0.6802647	0.0009437
1501	Scavenging by Class A Receptors	10	0.0003152	0.6578167	0.0025648
856	MET activates RAP1 and RAC1	10	0.0003164	0.6576284	0.0025648
25	ATF6 (ATF6-alpha) activates chaperone genes	10	0.0007206	0.6174928	0.0049796
480	Erythropoietin activates Phosphoinositide-3-kinase (PI3K)	11	0.0006335	0.5949020	0.0044579
1563	Signaling by FLT3 ITD and TKD mutants	15	0.0001385	0.5682268	0.0012914
1156	Platelet sensitization by LDL	16	0.0000890	0.5657638	0.0009194
939	Mitotic Telophase/Cytokinesis	13	0.0004961	0.5578227	0.0036102
1347	Regulation of IFNG signaling	14	0.0003033	0.5575525	0.0025002
598	GAB1 signalosome	14	0.0005680	0.5319325	0.0041019
871	Maturation of hRSV A proteins	13	0.0010328	0.5255758	0.0068178
1353	Regulation of MITF-M-dependent genes involved in lysosome biogenesis and autophagy	16	0.0004321	0.5081697	0.0032376
1424	Respiratory syncytial virus (RSV) genome replication, transcription and translation	16	0.0004760	0.5044498	0.0035034
965	NFE2L2 regulating anti-oxidant/detoxification enzymes	16	0.0006201	0.4941670	0.0044136
1804	Translocation of ZAP-70 to Immunological synapse	24	0.0000279	-0.4939627	0.0003889
1564	Signaling by FLT3 fusion proteins	18	0.0003256	0.4892447	0.0026283
1231	RHO GTPases Activate WASPs and WAVEs	35	0.0000012	0.4743035	0.0000363
747	Insulin receptor recycling	24	0.0001110	0.4557327	0.0010711
1003	Negative regulation of MET activity	18	0.0010432	0.4463229	0.0068626
308	Cross-presentation of soluble exogenous antigens (endosomes)	35	0.0000057	0.4431978	0.0001163
1229	RHO GTPases Activate ROCKs	18	0.0013233	0.4371033	0.0084174
612	GSK3B and BTRC:CUL1-mediated-degradation of NFE2L2	42	0.0000013	0.4311667	0.0000397
1599	Signaling by PDGFR in disease	19	0.0011411	0.4310614	0.0073808
1240	RHOBTB1 GTPase cycle	23	0.0003491	0.4306785	0.0027708
1416	Resolution of Abasic Sites (AP sites)	38	0.0000099	-0.4142377	0.0001711
1380	Regulation of activated PAK-2p34 by proteasome mediated degradation	37	0.0000134	0.4134310	0.0002208

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/crp_pod1_a_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
## 2/36 [checklibraries]            
## 3/36                             
## 4/36 [peek]                      
## 5/36                             
## 6/36 [metrics]                   
## 7/36                             
## 8/36 [scatterplot]

## 9/36                             
## 10/36 [contourplot]               
## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e7ddaca3a.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- crp_pod1_b_adj
myname <- "crp_pod1_b_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21313

## Note: no. genes in output = 21253

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

crp_pod1_b_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
479	Erythrocytes take up oxygen and release carbon dioxide	7	0.0002446	0.8004330	0.0038521
1739	Termination of O-glycan biosynthesis	15	0.0001146	0.5751640	0.0019143
180	CD22 mediated BCR regulation	58	0.0000000	0.5163091	0.0000000
1503	Scavenging of heme from plasma	70	0.0000000	0.4724193	0.0000000
271	Classical antibody-mediated complement activation	69	0.0000000	0.4468521	0.0000000
55	Activation of Matrix Metalloproteinases	20	0.0006118	0.4425093	0.0086419
567	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0000002	-0.4208630	0.0000060
141	BBSome-mediated cargo-targeting to cilium	23	0.0005186	-0.4180467	0.0075471
1793	Translation initiation complex formation	58	0.0000000	-0.4172406	0.0000013
72	Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	59	0.0000000	-0.4163075	0.0000011
159	Binding and Uptake of Ligands by Scavenger Receptors	90	0.0000000	0.4153255	0.0000000
809	L13a-mediated translational silencing of Ceruloplasmin expression	110	0.0000000	-0.4136069	0.0000000
305	Creation of C4 and C2 activators	71	0.0000000	0.4135334	0.0000001
1438	Ribosomal scanning and start codon recognition	58	0.0000001	-0.4110940	0.0000020
613	GTP hydrolysis and joining of the 60S ribosomal subunit	111	0.0000000	-0.4109705	0.0000000
554	Formation of a pool of free 40S subunits	100	0.0000000	-0.4085217	0.0000000
108	Antimicrobial peptides	33	0.0000673	0.4008311	0.0012377
754	Interaction between L1 and Ankyrins	26	0.0004072	0.4005131	0.0061109
216	Cap-dependent Translation Initiation	118	0.0000000	-0.3988083	0.0000000
491	Eukaryotic Translation Initiation	118	0.0000000	-0.3988083	0.0000000
368	Defective homologous recombination repair (HRR) due to BRCA2 loss of function	41	0.0000104	-0.3977868	0.0002442
404	Diseases of DNA Double-Strand Break Repair	41	0.0000104	-0.3977868	0.0002442
505	FCGR activation	76	0.0000000	0.3941056	0.0000001
1480	SRP-dependent cotranslational protein targeting to membrane	111	0.0000000	-0.3910537	0.0000000
1179	Presynaptic phase of homologous DNA pairing and strand exchange	40	0.0000198	-0.3898600	0.0004318
722	Impaired BRCA2 binding to RAD51	35	0.0000676	-0.3891090	0.0012377
926	Mitochondrial translation	96	0.0000000	-0.3863182	0.0000000
1338	Regulation of Complement cascade	96	0.0000000	0.3860799	0.0000000
1507	Selenocysteine synthesis	92	0.0000000	-0.3789498	0.0000000
739	Initial triggering of complement	79	0.0000000	0.3783444	0.0000002

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/crp_pod1_b_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
## 2/36 [checklibraries]            
## 3/36                             
## 4/36 [peek]                      
## 5/36                             
## 6/36 [metrics]                   
## 7/36                             
## 8/36 [scatterplot]

## 9/36                             
## 10/36 [contourplot]               
## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e3cf80106.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- dex_crplo_t0_adj
myname <- "dex_crplo_t0_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21935

## Note: no. genes in output = 21870

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

dex_crplo_t0_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
164	Biosynthesis of EPA-derived SPMs	6	0.0002574	0.8614770	0.0043894
165	Biosynthesis of Lipoxins (LX)	6	0.0003349	0.8454232	0.0052511
309	Cross-presentation of particulate exogenous antigens (phagosomes)	8	0.0002059	0.7576960	0.0036406
1532	Signal attenuation	9	0.0006864	0.6534468	0.0090592
108	Antimicrobial peptides	34	0.0000000	0.5571910	0.0000014
1417	Replacement of protamines by nucleosomes in the male pronucleus	13	0.0005311	0.5548970	0.0074698
1266	RNA Polymerase I Promoter Opening	17	0.0000926	0.5475409	0.0022968
1430	Response of EIF2AK1 (HRI) to heme deficiency	14	0.0007107	0.5225110	0.0093162
987	NR1H3 & NR1H2 regulate gene expression linked to cholesterol transport and efflux	32	0.0000005	-0.5122321	0.0000299
1703	TGFBR3 expression	20	0.0001040	-0.5012128	0.0025009
42	Activated PKN1 stimulates transcription of AR (androgen receptor) regulated genes KLK2 and KLK3	20	0.0005134	0.4486201	0.0073405
1818	Transport of Ribonucleoproteins into the Host Nucleus	32	0.0000149	-0.4422366	0.0005512
365	Defective TPR may confer susceptibility towards thyroid papillary carcinoma (TPC)	32	0.0000173	-0.4387936	0.0005858
1347	Regulation of Glucokinase by Glucokinase Regulatory Protein	32	0.0000173	-0.4387936	0.0005858
986	NR1H2 and NR1H3-mediated signaling	38	0.0000052	-0.4269638	0.0002237
1870	Vpr-mediated nuclear import of PICs	34	0.0000172	-0.4258456	0.0005858
762	Interferon alpha/beta signaling	64	0.0000000	-0.4004417	0.0000022
1355	Regulation of MECP2 expression and activity	29	0.0001919	-0.4000654	0.0035037
1406	Regulation of ornithine decarboxylase (ODC)	38	0.0000240	0.3959253	0.0007964
496	Export of Viral Ribonucleoproteins from Nucleus	33	0.0001075	-0.3895016	0.0025262
1499	SUMOylation of SUMOylation proteins	35	0.0000712	-0.3879159	0.0020175
962	NEP/NS2 Interacts with the Cellular Export Machinery	32	0.0001808	-0.3824068	0.0034493
990	NS1 Mediated Effects on Host Pathways	40	0.0000308	-0.3807306	0.0010060
1172	Postmitotic nuclear pore complex (NPC) reformation	27	0.0006655	-0.3783617	0.0088443
1385	Regulation of activated PAK-2p34 by proteasome mediated degradation	37	0.0000740	0.3764213	0.0020552
1049	Nuclear import of Rev protein	34	0.0001501	-0.3756021	0.0031108
99	Amyloid fiber formation	51	0.0000046	0.3707724	0.0002020
1827	Transport of the SLBP independent Mature mRNA	35	0.0001837	-0.3652864	0.0034655
380	Degradation of DVL	43	0.0000365	0.3638261	0.0011713
758	Interactions of Rev with host cellular proteins	37	0.0001313	-0.3632302	0.0028108

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/dex_crplo_t0_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 4/36 [peek]                      
## 5/36                             
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## 7/36                             
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## 9/36                             
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## 15/36                             
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## 17/36                             
## 18/36 [echart1d]                  
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## 20/36                             
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## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
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## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e48394c52.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- dex_crphi_t0_adj
myname <- "dex_crphi_t0_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21935

## Note: no. genes in output = 21870

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

dex_crphi_t0_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
1148	Phosphorylation of Emi1	6	0.0010267	-0.7738901	0.0048021
273	Classical antibody-mediated complement activation	70	0.0000000	-0.7615242	0.0000000
1508	Scavenging of heme from plasma	71	0.0000000	-0.7389982	0.0000000
307	Creation of C4 and C2 activators	72	0.0000000	-0.7354255	0.0000000
982	NR1H2 & NR1H3 regulate gene expression linked to lipogenesis	8	0.0004599	-0.7151336	0.0024348
742	Initial triggering of complement	80	0.0000000	-0.6920044	0.0000000
507	FCGR activation	77	0.0000000	-0.6874273	0.0000000
180	CD22 mediated BCR regulation	59	0.0000000	-0.6782653	0.0000000
659	Glycosphingolipid transport	7	0.0020856	-0.6716958	0.0089113
557	Formation of annular gap junctions	10	0.0002509	-0.6685544	0.0014389
1445	Role of LAT2/NTAL/LAB on calcium mobilization	78	0.0000000	-0.6454792	0.0000000
1837	Type I hemidesmosome assembly	8	0.0016043	-0.6441199	0.0071395
1845	Unwinding of DNA	12	0.0001961	-0.6207643	0.0011701
660	Glyoxylate metabolism and glycine degradation	13	0.0001076	-0.6202519	0.0007150
1446	Role of phospholipids in phagocytosis	89	0.0000000	-0.6104676	0.0000000
159	Binding and Uptake of Ligands by Scavenger Receptors	93	0.0000000	-0.5991865	0.0000000
994	Nef Mediated CD4 Down-regulation	9	0.0021593	-0.5904121	0.0091855
497	Expression and translocation of olfactory receptors	52	0.0000000	0.5867826	0.0000000
508	FCGR3A-mediated IL10 synthesis	100	0.0000000	-0.5835903	0.0000000
1437	Retrograde neurotrophin signalling	12	0.0004787	-0.5821743	0.0025206
547	Formation of ATP by chemiosmotic coupling	20	0.0000078	-0.5772723	0.0000776
504	FCERI mediated Ca+2 mobilization	93	0.0000000	-0.5727948	0.0000000
1343	Regulation of Complement cascade	97	0.0000000	-0.5670936	0.0000000
1724	TP53 Regulates Transcription of Genes Involved in G2 Cell Cycle Arrest	18	0.0000315	-0.5665843	0.0002650
1856	VLDLR internalisation and degradation	15	0.0001708	-0.5604545	0.0010480
1123	Pausing and recovery of Tat-mediated HIV elongation	30	0.0000001	-0.5556685	0.0000019
1739	Tat-mediated HIV elongation arrest and recovery	30	0.0000001	-0.5556685	0.0000019
287	Complement cascade	101	0.0000000	-0.5548043	0.0000000
509	FCGR3A-mediated phagocytosis	122	0.0000000	-0.5439483	0.0000000
826	Leishmania phagocytosis	122	0.0000000	-0.5439483	0.0000000

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/dex_crphi_t0_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 3/36                             
## 4/36 [peek]                      
## 5/36                             
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## 7/36                             
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## 9/36                             
## 10/36 [contourplot]               
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## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e3c8d2d45.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- dex_crplo_eos_adj
myname <- "dex_crplo_eos_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 22067

## Note: no. genes in output = 21999

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

dex_crplo_eos_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
180	CD163 mediating an anti-inflammatory response	9	0.0000764	0.7613056	0.0010317
1107	POLB-Dependent Long Patch Base Excision Repair	8	0.0009283	-0.6760152	0.0086365
1127	Peptide chain elongation	88	0.0000000	-0.6601717	0.0000000
495	Eukaryotic Translation Elongation	93	0.0000000	-0.6528736	0.0000000
559	Formation of a pool of free 40S subunits	100	0.0000000	-0.6440331	0.0000000
1454	SARS-CoV-1 modulates host translation machinery	36	0.0000000	-0.6415031	0.0000000
497	Eukaryotic Translation Termination	92	0.0000000	-0.6408712	0.0000000
1867	Viral mRNA Translation	88	0.0000000	-0.6407606	0.0000000
1514	Selenocysteine synthesis	92	0.0000000	-0.6337621	0.0000000
1039	Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	94	0.0000000	-0.5896487	0.0000000
619	GTP hydrolysis and joining of the 60S ribosomal subunit	111	0.0000000	-0.5855189	0.0000000
1814	Translocation of ZAP-70 to Immunological synapse	24	0.0000007	-0.5851498	0.0000163
815	L13a-mediated translational silencing of Ceruloplasmin expression	110	0.0000000	-0.5842985	0.0000000
220	Cap-dependent Translation Initiation	118	0.0000000	-0.5834045	0.0000000
496	Eukaryotic Translation Initiation	118	0.0000000	-0.5834045	0.0000000
182	CD22 mediated BCR regulation	58	0.0000000	0.5790498	0.0000000
1433	Response of EIF2AK4 (GCN2) to amino acid deficiency	100	0.0000000	-0.5728307	0.0000000
572	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0000000	-0.5725333	0.0000000
1510	Scavenging of heme from plasma	70	0.0000000	0.5710768	0.0000000
1460	SARS-CoV-2 modulates host translation machinery	49	0.0000000	-0.5654447	0.0000000
1487	SRP-dependent cotranslational protein targeting to membrane	111	0.0000000	-0.5445330	0.0000000
275	Classical antibody-mediated complement activation	69	0.0000000	0.5380136	0.0000000
504	FASTK family proteins regulate processing and stability of mitochondrial RNAs	19	0.0000547	0.5345577	0.0007713
1513	Selenoamino acid metabolism	115	0.0000000	-0.5290464	0.0000000
1038	Nonsense Mediated Decay (NMD) enhanced by the Exon Junction Complex (EJC)	114	0.0000000	-0.5282181	0.0000000
1040	Nonsense-Mediated Decay (NMD)	114	0.0000000	-0.5282181	0.0000000
309	Creation of C4 and C2 activators	71	0.0000000	0.5102152	0.0000000
1447	Role of LAT2/NTAL/LAB on calcium mobilization	77	0.0000000	0.5055883	0.0000000
1082	PD-1 signaling	28	0.0000038	-0.5043401	0.0000740
1396	Regulation of expression of SLITs and ROBOs	149	0.0000000	-0.5008610	0.0000000

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/dex_crplo_eos_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 4/36 [peek]                      
## 5/36                             
## 6/36 [metrics]                   
## 7/36                             
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## 9/36                             
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## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
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## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e579cc2b0.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- dex_crphi_eos_adj
myname <- "dex_crphi_eos_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 22067

## Note: no. genes in output = 21999

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

dex_crphi_eos_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
180	CD163 mediating an anti-inflammatory response	9	0.0000714	0.7644081	0.0051770
309	Creation of C4 and C2 activators	71	0.0000000	-0.4774974	0.0000000
745	Initial triggering of complement	79	0.0000000	-0.4725966	0.0000000
1814	Translocation of ZAP-70 to Immunological synapse	24	0.0000615	-0.4724346	0.0047512
275	Classical antibody-mediated complement activation	69	0.0000000	-0.4676725	0.0000000
1510	Scavenging of heme from plasma	70	0.0000000	-0.4449581	0.0000001
344	DNA strand elongation	32	0.0000948	-0.3986434	0.0057782
182	CD22 mediated BCR regulation	58	0.0000002	-0.3920388	0.0000514
693	Hedgehog ligand biogenesis	47	0.0000112	0.3702934	0.0011368
1065	Olfactory Signaling Pathway	61	0.0000006	0.3699278	0.0000930
510	FCGR activation	76	0.0000000	-0.3687932	0.0000087
500	Expression and translocation of olfactory receptors	56	0.0000018	0.3685832	0.0002346
988	NR1H2 and NR1H3-mediated signaling	39	0.0001112	-0.3575802	0.0062246
1448	Role of phospholipids in phagocytosis	88	0.0000000	-0.3538053	0.0000037
700	Hh mutants are degraded by ERAD	42	0.0000823	0.3510823	0.0056789
699	Hh mutants abrogate ligand secretion	43	0.0000723	0.3496994	0.0051770
27	AUF1 (hnRNP D0) binds and destabilizes mRNA	42	0.0000909	0.3489526	0.0057782
1447	Role of LAT2/NTAL/LAB on calcium mobilization	77	0.0000004	-0.3337050	0.0000720
383	Degradation of GLI1 by the proteasome	46	0.0000957	0.3324038	0.0057782
618	GSK3B and BTRC:CUL1-mediated-degradation of NFE2L2	42	0.0002008	0.3315051	0.0099494
57	Activation of NF-kappaB in B cells	54	0.0000406	0.3228070	0.0035634
289	Complement cascade	100	0.0000000	-0.3199607	0.0000088
1345	Regulation of Complement cascade	96	0.0000002	-0.3050686	0.0000514
160	Binding and Uptake of Ligands by Scavenger Receptors	94	0.0000004	-0.3024006	0.0000720
434	Downstream signaling events of B Cell Receptor (BCR)	68	0.0000360	0.2896853	0.0033128
511	FCGR3A-mediated IL10 synthesis	99	0.0000008	-0.2865163	0.0001194
508	FCERI mediated MAPK activation	93	0.0000021	-0.2846404	0.0002514
3	ABC transporter disorders	60	0.0001392	0.2843065	0.0072204
507	FCERI mediated Ca+2 mobilization	92	0.0000041	-0.2776490	0.0004452
458	ER-Phagosome pathway	75	0.0001177	0.2571380	0.0063152

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/dex_crphi_eos_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
## 2/36 [checklibraries]            
## 3/36                             
## 4/36 [peek]                      
## 5/36                             
## 6/36 [metrics]                   
## 7/36                             
## 8/36 [scatterplot]

## 9/36                             
## 10/36 [contourplot]               
## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

## 15/36                             
## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e65f506c6.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- dex_crplo_pod1_adj
myname <- "dex_crplo_pod1_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21313

## Note: no. genes in output = 21253

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

dex_crplo_pod1_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
484	Establishment of Sister Chromatid Cohesion	11	0.0000090	-0.7731595	0.0012282
759	Interferon alpha/beta signaling	63	0.0000000	-0.4161846	0.0000070
722	Impaired BRCA2 binding to RAD51	35	0.0000866	-0.3833403	0.0063996
717	ISG15 antiviral mechanism	72	0.0000649	-0.2722067	0.0049850
97	Amplification of signal from unattached kinetochores via a MAD2 inhibitory signal	90	0.0000538	-0.2462505	0.0047018
98	Amplification of signal from the kinetochores	90	0.0000538	-0.2462505	0.0047018
1420	Resolution of Sister Chromatid Cohesion	115	0.0000116	-0.2366988	0.0014833
938	Mitotic Spindle Checkpoint	107	0.0000392	-0.2300517	0.0044343
1521	Separation of Sister Chromatids	167	0.0000085	-0.1996239	0.0012282
231	Cell Cycle Checkpoints	245	0.0000001	-0.1993643	0.0000359
109	Antiviral mechanism by IFN-stimulated genes	140	0.0000467	-0.1992936	0.0046732
933	Mitotic G1 phase and G1/S transition	138	0.0001316	-0.1885074	0.0093603
935	Mitotic Metaphase and Anaphase	211	0.0000029	-0.1868995	0.0006128
932	Mitotic Anaphase	210	0.0000033	-0.1862219	0.0006318
758	Interferon Signaling	237	0.0000028	-0.1767783	0.0006128
936	Mitotic Prometaphase	192	0.0000607	-0.1678245	0.0048585
498	Extracellular matrix organization	213	0.0000456	0.1620705	0.0046732
269	Class I MHC mediated antigen processing & presentation	343	0.0000047	-0.1438446	0.0008209
232	Cell Cycle, Mitotic	487	0.0000003	-0.1363729	0.0000700
839	M Phase	345	0.0000231	-0.1326323	0.0027706
230	Cell Cycle	609	0.0000001	-0.1267052	0.0000359
881	Membrane Trafficking	575	0.0000080	-0.1089704	0.0012282
1268	RNA Polymerase II Transcription	1185	0.0000000	-0.1039885	0.0000016
628	Gene expression (Transcription)	1391	0.0000000	-0.0995572	0.0000010
630	Generic Transcription Pathway	1067	0.0000001	-0.0958953	0.0000394
900	Metabolism of proteins	1761	0.0000487	-0.0583476	0.0046732
719	Immune System	1828	0.0000601	-0.0566673	0.0048585

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/dex_crplo_pod1_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 17/36                             
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## 22/36                             
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## 26/36                             
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## 28/36                             
## 29/36 [detailed_geneset_reports1d]

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## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e7f51c17.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

de <- dex_crphi_pod1_adj
myname <- "dex_crphi_pod1_adj"

m <- mitch_import(x=de, DEtype="deseq2", geneTable=gt )

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 21313

## Note: no. genes in output = 21253

## Note: estimated proportion of input genes in output = 0.997

mres <- mitch_calc(x=m,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

mtop <- head(subset (mres$enrichment_result,p.adjustANOVA<0.01),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

dex_crphi_pod1_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
180	CD22 mediated BCR regulation	58	0.0000000	-0.8108614	0.0000000
1503	Scavenging of heme from plasma	70	0.0000000	-0.7763233	0.0000000
505	FCGR activation	76	0.0000000	-0.7704262	0.0000000
271	Classical antibody-mediated complement activation	69	0.0000000	-0.7520661	0.0000000
1831	Type I hemidesmosome assembly	8	0.0003991	-0.7228054	0.0075914
305	Creation of C4 and C2 activators	71	0.0000000	-0.7183099	0.0000000
1440	Role of LAT2/NTAL/LAB on calcium mobilization	77	0.0000000	-0.6841241	0.0000000
1839	Unwinding of DNA	12	0.0000607	-0.6684557	0.0015339
739	Initial triggering of complement	79	0.0000000	-0.6400733	0.0000000
502	FCERI mediated Ca+2 mobilization	92	0.0000000	-0.6254893	0.0000000
506	FCGR3A-mediated IL10 synthesis	99	0.0000000	-0.6235094	0.0000000
105	Antigen activates B Cell Receptor (BCR) leading to generation of second messengers	83	0.0000000	-0.6230321	0.0000000
1441	Role of phospholipids in phagocytosis	88	0.0000000	-0.6219713	0.0000000
159	Binding and Uptake of Ligands by Scavenger Receptors	90	0.0000000	-0.5895184	0.0000000
283	Common Pathway of Fibrin Clot Formation	13	0.0003274	-0.5754020	0.0067621
503	FCERI mediated MAPK activation	93	0.0000000	-0.5571671	0.0000000
507	FCGR3A-mediated phagocytosis	121	0.0000000	-0.5536486	0.0000000
823	Leishmania phagocytosis	121	0.0000000	-0.5536486	0.0000000
1114	Parasite infection	121	0.0000000	-0.5536486	0.0000000
1379	Regulation of actin dynamics for phagocytic cup formation	123	0.0000000	-0.5387347	0.0000000
592	G1/S-Specific Transcription	29	0.0000010	-0.5249652	0.0000372
1338	Regulation of Complement cascade	96	0.0000000	-0.5130640	0.0000000
103	Anti-inflammatory response favouring Leishmania parasite infection	131	0.0000000	-0.5130066	0.0000000
822	Leishmania parasite growth and survival	131	0.0000000	-0.5130066	0.0000000
1768	Transcription of E2F targets under negative control by DREAM complex	19	0.0001969	-0.4932953	0.0042972
285	Complement cascade	100	0.0000000	-0.4923406	0.0000000
588	G0 and Early G1	27	0.0000221	-0.4716543	0.0006838
541	Fcgamma receptor (FCGR) dependent phagocytosis	147	0.0000000	-0.4700588	0.0000000
1709	TNFs bind their physiological receptors	25	0.0000584	-0.4643188	0.0014952
504	FCERI mediated NF-kB activation	129	0.0000000	-0.4586517	0.0000000

vec <- mtop$s.dist
names(vec) <- mtop$set
vec <- sort(vec)
par( mar = c(5.1, 25.1, 4.1, 2.1) )
barplot(vec,horiz=TRUE,las=1,cex.names=0.7,xlab="ES",main=myname)

par( mar = c(5.1, 4.1, 4.1, 2.1) )
mitch_report(res=mres,outfile=paste(myname,"_mitchreport.html",sep=""),overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/dex_crphi_pod1_adj_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 7/36                             
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## 9/36                             
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## 13/36                             
## 14/36 [input_geneset_metrics2]

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## 16/36 [input_geneset_metrics3]

## 17/36                             
## 18/36 [echart1d]                  
## 19/36 [echart2d]                  
## 20/36                             
## 21/36 [heatmap]                   
## 22/36                             
## 23/36 [effectsize]                
## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]

## 30/36                             
## 31/36 [detailed_geneset_reports2d]
## 32/36                             
## 33/36 [network]

## 34/36                             
## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e1a9ff2cc.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

Multi-contrast enrichment anslysis.

l2 <- list("crp_t0_a"=crp_t0_a_adj,
"crp t0 b"=crp_t0_b_adj,
"crp eos a"=crp_eos_a_adj,
"crp eos b"=crp_eos_b_adj,
"crp _pod1 a"=crp_pod1_a_adj,
"crp pod1 b"=crp_pod1_b_adj,
"dex crplo t0"=dex_crplo_t0_adj,
"dex crphi t0"=dex_crphi_t0_adj,
"dex crplo eos"=dex_crplo_eos_adj,
"dex crphi eos"=dex_crphi_eos_adj,
"dex crplo pod1"=dex_crplo_pod1_adj,
"dex crphi pod1"=dex_crphi_pod1_adj)

m2 <- mitch_import(x=l2, DEtype="deseq2", geneTable=gt )

## Note: Mean no. genes in input = 21771.6666666667

## Note: no. genes in output = 21032

## Note: estimated proportion of input genes in output = 0.966

mm2 <- mitch_calc(x=m2,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be 
##             statistically significant.

top <- head(subset (mm2$enrichment_result,p.adjustMANOVA<0.01),50)
top <- top[,c(1,4:15)]
rownames(top) <- top[,1]
top[,1] = NULL
colnames(top) <- gsub("^s\\.","",colnames(top))

colfunc <- colorRampPalette(c("blue", "white", "red"))

heatmap.2(as.matrix(top),trace="none",col=colfunc(25),scale="none",
    margins = c(7,20), cexRow=0.6, cexCol=0.7 )

as.matrix(top) |>
  kbl(caption="Top REACTOMEs in multi enrichment analysis") |>
  kable_paper("hover", full_width = F)

Top REACTOMEs in multi enrichment analysis

	crp_t0_a	crp.t0.b	crp.eos.a	crp.eos.b	crp._pod1.a	crp.pod1.b	dex.crplo.t0	dex.crphi.t0	dex.crplo.eos	dex.crphi.eos	dex.crplo.pod1	dex.crphi.pod1
CD163 mediating an anti-inflammatory response	-0.2419378	0.1677725	0.0896119	0.4071181	0.8194563	0.6062476	0.4283557	-0.2133395	0.8104785	0.7892290	0.2167761	0.3812548
Peptide chain elongation	-0.8125666	0.1859676	-0.6871225	-0.8502657	-0.3450191	-0.3654733	0.3634176	-0.3762251	-0.6537105	0.0018291	0.0459304	0.0140604
Erythrocytes take up oxygen and release carbon dioxide	0.4188959	0.5443656	0.3304162	0.5119959	0.5927977	0.8020588	0.4363173	-0.4133243	0.4066791	0.6093222	-0.0500696	-0.2800272
CD22 mediated BCR regulation	-0.5428660	0.3039132	-0.5283976	0.2818184	-0.3706660	0.5136633	0.0573958	-0.6858516	0.5820036	-0.3880618	0.1344014	-0.8074299
Classical antibody-mediated complement activation	-0.6058579	0.2337410	-0.5714853	0.2366283	-0.3002149	0.4439880	0.0602910	-0.7703051	0.5414197	-0.4646803	0.1355489	-0.7482238
Scavenging of heme from plasma	-0.5659682	0.2723467	-0.5353940	0.2745189	-0.2956783	0.4701209	0.1023231	-0.7466191	0.5742990	-0.4416567	0.1230360	-0.7729139
Eukaryotic Translation Elongation	-0.7937420	0.1857523	-0.6691074	-0.8412016	-0.3357388	-0.3537509	0.3476714	-0.3682478	-0.6461661	-0.0055905	0.0392540	-0.0076149
Viral mRNA Translation	-0.8026062	0.1654497	-0.6743161	-0.8344531	-0.3144640	-0.3588418	0.3511688	-0.3616681	-0.6341420	0.0194944	0.0192167	0.0189950
Cohesin Loading onto Chromatin	0.1660927	-0.6739321	0.6198173	0.4808677	0.7625630	-0.4166968	-0.5487204	-0.0164114	0.1694320	0.1614214	-0.6715060	0.0929693
Formation of a pool of free 40S subunits	-0.7830355	0.1421008	-0.6549704	-0.8461827	-0.2844472	-0.4003292	0.3382707	-0.3545033	-0.6368703	0.0320315	0.0164165	0.0377496
SARS-CoV-1 modulates host translation machinery	-0.7824639	0.1985907	-0.6437972	-0.8169784	-0.3477541	-0.3338414	0.3547872	-0.3464813	-0.6330677	0.0455431	0.0399468	-0.0037467
Eukaryotic Translation Termination	-0.7785899	0.1620896	-0.6615809	-0.7963908	-0.3190938	-0.3653567	0.3104279	-0.3567894	-0.6342261	0.0174005	0.0154999	0.0107056
Creation of C4 and C2 activators	-0.5880341	0.2239372	-0.5416781	0.2122167	-0.2969796	0.4103207	0.0599888	-0.7429144	0.5134802	-0.4746466	0.1390734	-0.7140567
Selenocysteine synthesis	-0.7633151	0.1564065	-0.6536759	-0.8104995	-0.3218614	-0.3698686	0.3082701	-0.3558805	-0.6268407	0.0030599	0.0162083	0.0208535
Formation of ATP by chemiosmotic coupling	-0.7950076	0.0566914	-0.8110603	-0.7102037	0.1571959	-0.2972444	0.4226728	-0.5712212	-0.2826813	0.1463354	0.0368980	0.0303017
Phosphorylation of Emi1	-0.3700339	0.1144615	-0.3859190	0.3340150	-0.1590095	0.6344684	-0.3729668	-0.7697454	0.2914011	-0.4468277	-0.0672184	-0.7811757
Fructose metabolism	-0.6620078	0.2944726	-0.2563411	-0.3798267	-0.4615662	-0.3622286	0.4716902	-0.3365857	-0.2656361	-0.6766163	0.6105181	0.2846883
Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	-0.7615049	0.1435665	-0.6484052	-0.7688462	-0.3022086	-0.3551181	0.3014979	-0.3495443	-0.5822448	0.0353782	0.0162032	0.0230454
L13a-mediated translational silencing of Ceruloplasmin expression	-0.7470103	0.0927389	-0.6260864	-0.8031015	-0.2257210	-0.4060178	0.3342816	-0.3319919	-0.5761690	0.0547192	-0.0163040	0.0421208
GTP hydrolysis and joining of the 60S ribosomal subunit	-0.7325816	0.0838430	-0.6228111	-0.8006118	-0.2132866	-0.4033814	0.3255468	-0.3164620	-0.5774157	0.0609832	-0.0224383	0.0436922
Cap-dependent Translation Initiation	-0.7175315	0.0864030	-0.6163307	-0.8011495	-0.2145514	-0.3913999	0.3284017	-0.3228252	-0.5752437	0.0523433	-0.0046346	0.0433546
Eukaryotic Translation Initiation	-0.7175315	0.0864030	-0.6163307	-0.8011495	-0.2145514	-0.3913999	0.3284017	-0.3228252	-0.5752437	0.0523433	-0.0046346	0.0433546
FCGR activation	-0.5405360	0.2090382	-0.4379577	0.3015807	-0.2551478	0.3911279	0.0457693	-0.6920552	0.4974077	-0.3641533	0.0269218	-0.7671168
SRP-dependent cotranslational protein targeting to membrane	-0.7526058	0.0568771	-0.6580068	-0.7531116	-0.1997323	-0.3831678	0.3132709	-0.3599647	-0.5357640	0.0936326	-0.0594841	-0.0511363
Establishment of Sister Chromatid Cohesion	0.1440075	-0.6911660	0.3358676	0.3256181	0.6824215	-0.4116187	-0.4671216	-0.0020369	0.2428697	0.0274574	-0.7725910	-0.1275132
G2/M DNA replication checkpoint	-0.4509535	-0.2228849	-0.2255481	0.1675655	0.3647406	0.5400200	-0.1401722	-0.6120797	0.5925049	-0.1351691	-0.3613164	-0.7502259
Response of EIF2AK4 (GCN2) to amino acid deficiency	-0.7169855	0.1514437	-0.6232559	-0.7559477	-0.2503200	-0.3326906	0.3472913	-0.3133591	-0.5649525	0.0240628	0.0154273	0.0097787
NFE2L2 regulates pentose phosphate pathway genes	-0.3371504	0.2299634	0.4170710	0.4182006	0.7758633	0.4873478	0.2602740	-0.4748740	0.5950342	0.3722175	0.2340420	0.1057958
Initial triggering of complement	-0.5446118	0.2303813	-0.5127752	0.1644885	-0.2805498	0.3753423	0.0625277	-0.6967631	0.4467601	-0.4692648	0.1443296	-0.6351079
Protein repair	-0.6190272	0.0014902	-0.1150480	-0.1028885	0.4722407	0.1703129	0.7825074	-0.2929706	0.5411554	0.4330511	0.0329592	-0.5610673
Formation of the ternary complex, and subsequently, the 43S complex	-0.6965415	0.0761520	-0.5713208	-0.7781653	-0.1982513	-0.4180860	0.3084182	-0.2897458	-0.5632276	0.0862769	-0.0426875	0.0370952
Defective binding of VWF variant to GPIb:IX:V	0.2089789	0.2105769	-0.2831122	-0.4076378	0.2028915	0.5959481	0.3907643	0.0810292	0.5490179	0.4406430	0.7476388	-0.3901175
Enhanced binding of GP1BA variant to VWF multimer:collagen	0.2089789	0.2105769	-0.2831122	-0.4076378	0.2028915	0.5959481	0.3907643	0.0810292	0.5490179	0.4406430	0.7476388	-0.3901175
Role of LAT2/NTAL/LAB on calcium mobilization	-0.5186343	0.1807685	-0.4007306	0.2925855	-0.2032454	0.3157066	0.0753597	-0.6485493	0.5086346	-0.3285192	0.0197268	-0.6795768
Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	-0.6781495	0.0270348	-0.5499460	-0.7320316	-0.1406983	-0.4136060	0.3097049	-0.2845458	-0.4856454	0.1017814	-0.0476003	0.0689191
Modulation by Mtb of host immune system	-0.8150773	-0.0349992	-0.4537252	-0.6214574	0.1229625	-0.2785188	0.4998743	-0.2806659	0.0020044	0.4609546	-0.1457109	-0.0266825
Translation initiation complex formation	-0.6740414	0.0296574	-0.5467377	-0.7274754	-0.1381513	-0.4145510	0.3027311	-0.2867886	-0.4873439	0.1088967	-0.0610510	0.0592556
Ribosomal scanning and start codon recognition	-0.6662255	0.0269562	-0.5559708	-0.7281840	-0.1250859	-0.4083693	0.2987689	-0.2754247	-0.4869017	0.1119613	-0.0600810	0.0702742
Phosphate bond hydrolysis by NUDT proteins	-0.7170036	-0.1221879	-0.5331952	-0.7682215	-0.0642432	-0.4846951	0.2694140	-0.1544896	-0.0441991	0.2996093	-0.1991575	0.0517547
NR1H2 & NR1H3 regulate gene expression linked to lipogenesis	-0.5695277	0.1899853	-0.2834499	0.0876617	-0.0164574	0.3894240	-0.2341015	-0.7106521	-0.3078030	-0.6514697	0.3870814	0.0995291
SARS-CoV-2 modulates host translation machinery	-0.6054668	0.1771181	-0.5917181	-0.6844793	-0.2600949	-0.2685410	0.2852523	-0.2885767	-0.5566479	0.0148721	0.0417899	0.0057919
Selenoamino acid metabolism	-0.6608377	0.0921770	-0.5610898	-0.6952100	-0.2299757	-0.3152133	0.2569524	-0.3057746	-0.5207703	0.0335160	-0.0073369	0.0511655
Type I hemidesmosome assembly	-0.2403563	0.1954909	-0.0031036	0.4687619	0.1227645	0.5536411	-0.0888152	-0.6382468	-0.1166405	-0.4763009	0.0843203	-0.7222460
Mitochondrial translation elongation	-0.5637910	0.0983202	-0.6863517	-0.6750040	-0.1960038	-0.3562018	0.1953056	-0.3690935	-0.4598319	0.0665351	-0.0071319	-0.0872250
Mitochondrial translation initiation	-0.5407177	0.0718471	-0.6742442	-0.6913507	-0.2064506	-0.3705249	0.1743079	-0.3467482	-0.4661669	0.0721983	-0.0241853	-0.1093242
Signal attenuation	-0.4370399	0.0648655	-0.0165269	0.4111846	0.4960229	0.3483962	0.6542411	-0.1553801	0.5205146	0.4859281	0.1917424	0.2599640
Regulation of NFE2L2 gene expression	0.0453886	0.4146689	0.2340658	0.7166215	0.3268170	0.5222722	-0.4431602	-0.5877331	0.1243579	0.0270286	0.3295757	0.0677440
Regulation of activated PAK-2p34 by proteasome mediated degradation	-0.5980381	0.0571346	-0.4673378	-0.6021009	0.4164788	-0.1671942	0.3784337	-0.3470260	-0.4161544	0.3441450	-0.1734866	-0.2023995
Vpu mediated degradation of CD4	-0.5854247	0.0364309	-0.4621699	-0.6414238	0.3812443	-0.2062263	0.3354073	-0.3555141	-0.4720145	0.2935252	-0.1675369	-0.1872236
Vif-mediated degradation of APOBEC3G	-0.5933309	0.0662363	-0.5018841	-0.6216915	0.3534325	-0.1666672	0.3565721	-0.3648242	-0.4121290	0.3276654	-0.1441791	-0.2207369

mitch_report(res=mm2,outfile="multireactomestratified_all_mitchreport.html",overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpODzriF/multireactomestratified_all_mitchreport.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/36                             
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## 7/36                             
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## 9/36                             
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## 11/36                             
## 12/36 [input_geneset_metrics1]    
## 13/36                             
## 14/36 [input_geneset_metrics2]

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## 17/36                             
## 18/36 [echart1d]                  
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## 21/36 [heatmap]

## 22/36                             
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## 24/36                             
## 25/36 [results_table]             
## 26/36                             
## 27/36 [results_table_complete]    
## 28/36                             
## 29/36 [detailed_geneset_reports1d]
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## 31/36 [detailed_geneset_reports2d]

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## 33/36 [network]                   
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## 35/36 [session_info]              
## 36/36

## output file: /paddi-genomics/dge/mitch.knit.md

## /usr/bin/pandoc +RTS -K512m -RTS /paddi-genomics/dge/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpODzriF/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --syntax-highlighting=none --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpODzriF/rmarkdown-str1a3e6e4bc709.html

## 
## Output created: /tmp/RtmpODzriF/mitch_report.html

## [1] TRUE

This might work better if we work on each timepoint separately.

l2 <- list("crp_t0_a"=crp_t0_a_adj, "crp t0 b"=crp_t0_b_adj,
  "dex crplo t0"=dex_crplo_t0_adj, "dex crphi t0"=dex_crphi_t0_adj)
m2 <- mitch_import(x=l2, DEtype="deseq2", geneTable=gt )

## Note: Mean no. genes in input = 21935

## Note: no. genes in output = 21870

## Note: estimated proportion of input genes in output = 0.997

mm2 <- mitch_calc(x=m2,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be 
##             statistically significant.

top <- head(subset (mm2$enrichment_result,p.adjustMANOVA<0.01),50)
top <- top[,c(1,4:7)]
rownames(top) <- top[,1]
top[,1] = NULL
colnames(top) <- gsub("^s\\.","",colnames(top))
colfunc <- colorRampPalette(c("blue", "white", "red"))
heatmap.2(as.matrix(top),trace="none",col=colfunc(25),scale="none",
    margins = c(7,20), cexRow=0.6, cexCol=0.7 )

as.matrix(top) |>
  kbl(caption="Top REACTOMEs in multi enrichment analysis stratified t0") |>
  kable_paper("hover", full_width = F)

Top REACTOMEs in multi enrichment analysis stratified t0

	crp_t0_a	crp.t0.b	dex.crplo.t0	dex.crphi.t0
Formation of ATP by chemiosmotic coupling	-0.7990755	0.0544211	0.4209336	-0.5772723
Protein repair	-0.6253811	-0.0012654	0.7806592	-0.3025521
Formation of annular gap junctions	-0.7471089	0.1116651	0.1898628	-0.6685544
Glycosphingolipid transport	-0.7715383	0.0083442	0.0216347	-0.6716958
Modulation by Mtb of host immune system	-0.8191857	-0.0374736	0.4977686	-0.2874851
Peptide chain elongation	-0.8159548	0.1840320	0.3611057	-0.3851664
Classical antibody-mediated complement activation	-0.5802202	0.2412254	0.0553958	-0.7615242
Viral mRNA Translation	-0.8061728	0.1635152	0.3489049	-0.3707452
NR1H2 & NR1H3 regulate gene expression linked to lipogenesis	-0.5768914	0.1882948	-0.2344365	-0.7151336
Eukaryotic Translation Elongation	-0.7971247	0.1838084	0.3454094	-0.3770728
Scavenging of heme from plasma	-0.5421046	0.2787239	0.0960407	-0.7389982
Creation of C4 and C2 activators	-0.5637482	0.2314025	0.0552433	-0.7354255
SARS-CoV-1 modulates host translation machinery	-0.7859607	0.1967472	0.3526355	-0.3557321
Formation of a pool of free 40S subunits	-0.7868622	0.1401656	0.3359993	-0.3634215
Formyl peptide receptors bind formyl peptides and many other ligands	-0.6187166	-0.2694768	0.5605883	-0.3120275
Eukaryotic Translation Termination	-0.7823319	0.1601639	0.3082771	-0.3658222
Selenocysteine synthesis	-0.7670404	0.1543654	0.3061397	-0.3647616
Erythrocytes take up oxygen and release carbon dioxide	0.4114388	0.5430636	0.4343869	-0.4185349
Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	-0.7653665	0.1415882	0.2993940	-0.3584491
CD22 mediated BCR regulation	-0.5139632	0.3109308	0.0517473	-0.6782653
Initial triggering of complement	-0.5247705	0.2368196	0.0580966	-0.6920044
SRP-dependent cotranslational protein targeting to membrane	-0.7565157	0.0546658	0.3111113	-0.3687099
Glyoxylate metabolism and glycine degradation	-0.5337033	0.2108988	0.3005585	-0.6202519
L13a-mediated translational silencing of Ceruloplasmin expression	-0.7511549	0.0906331	0.3320219	-0.3408223
VLDLR internalisation and degradation	-0.6602151	0.1634927	0.1365576	-0.5604545
FCGR activation	-0.5201271	0.2162752	0.0415819	-0.6874273
Cohesin Loading onto Chromatin	0.1552333	-0.6764959	-0.5483898	-0.0270265
Response of EIF2AK4 (GCN2) to amino acid deficiency	-0.7211915	0.1495284	0.3450633	-0.3223475
GTP hydrolysis and joining of the 60S ribosomal subunit	-0.7368608	0.0817338	0.3233130	-0.3252749
Pentose phosphate pathway	-0.6339634	-0.0634931	0.3574528	-0.4669196
Cap-dependent Translation Initiation	-0.7219992	0.0842886	0.3262208	-0.3316587
Eukaryotic Translation Initiation	-0.7219992	0.0842886	0.3262208	-0.3316587
Synthesis of PIPs at the late endosome membrane	0.3589327	-0.6226559	-0.3514633	0.3058653
Retrograde neurotrophin signalling	-0.5940617	0.0922088	0.1446610	-0.5821743
Regulation of NFE2L2 gene expression	0.0365246	0.4139146	-0.4436465	-0.5930038
Establishment of Sister Chromatid Cohesion	0.1342364	-0.6938228	-0.4668973	-0.0118320
Role of LAT2/NTAL/LAB on calcium mobilization	-0.4989422	0.1885272	0.0703246	-0.6454792
RNA Polymerase I Promoter Opening	-0.5188250	0.0505355	0.5475409	-0.3585670
Formation of the ternary complex, and subsequently, the 43S complex	-0.7012318	0.0742014	0.3062783	-0.2988033
Synthesis of PIPs at the early endosome membrane	0.2633042	-0.6025613	-0.4431912	0.2021655
Abortive elongation of HIV-1 transcript in the absence of Tat	-0.5285872	0.2631721	0.1608479	-0.5412563
Hyaluronan uptake and degradation	-0.5253988	0.1091667	0.3683396	-0.4845747
Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	-0.6829076	0.0248739	0.3076049	-0.2933592
Regulation of ornithine decarboxylase (ODC)	-0.6036721	0.0282926	0.3959253	-0.3507285
Translation initiation complex formation	-0.6788481	0.0275110	0.3006396	-0.2955570
Pausing and recovery of Tat-mediated HIV elongation	-0.5109310	0.2270940	0.1200458	-0.5556685
Tat-mediated HIV elongation arrest and recovery	-0.5109310	0.2270940	0.1200458	-0.5556685
Regulation of activated PAK-2p34 by proteasome mediated degradation	-0.6036870	0.0550258	0.3764213	-0.3545204
Gluconeogenesis	-0.5070297	0.2418027	0.2515530	-0.5037491
Vif-mediated degradation of APOBEC3G	-0.5989426	0.0641673	0.3546267	-0.3722895

#mitch_report(res=mm2,outfile="multireactomestratified_t0_mitchreport.html",overwrite=TRUE)

l2 <- list("crp_eos_a"=crp_eos_a_adj, "crp eos b"=crp_eos_b_adj,
  "dex crplo eos"=dex_crplo_eos_adj, "dex crphi eos"=dex_crphi_eos_adj)
m2 <- mitch_import(x=l2, DEtype="deseq2", geneTable=gt )

## Note: Mean no. genes in input = 22067

## Note: no. genes in output = 21999

## Note: estimated proportion of input genes in output = 0.997

mm2 <- mitch_calc(x=m2,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be 
##             statistically significant.

top <- head(subset (mm2$enrichment_result,p.adjustMANOVA<0.01),50)
top <- top[,c(1,4:7)]
rownames(top) <- top[,1]
top[,1] = NULL
colnames(top) <- gsub("^s\\.","",colnames(top))
colfunc <- colorRampPalette(c("blue", "white", "red"))
heatmap.2(as.matrix(top),trace="none",col=colfunc(25),scale="none",
    margins = c(7,20), cexRow=0.6, cexCol=0.7 )

as.matrix(top) |>
  kbl(caption="Top REACTOMEs in multi enrichment analysis stratified EOS") |>
  kable_paper("hover", full_width = F)

Top REACTOMEs in multi enrichment analysis stratified EOS

	crp_eos_a	crp.eos.b	dex.crplo.eos	dex.crphi.eos
RUNX1 regulates transcription of genes involved in BCR signaling	0.5562679	0.5473408	0.7498750	0.7756407
Peptide chain elongation	-0.6817705	-0.8467468	-0.6601717	-0.0088239
Eukaryotic Translation Elongation	-0.6645020	-0.8382493	-0.6528736	-0.0159724
Formation of a pool of free 40S subunits	-0.6511777	-0.8436038	-0.6440331	0.0213398
Viral mRNA Translation	-0.6691149	-0.8310977	-0.6407606	0.0086248
SARS-CoV-1 modulates host translation machinery	-0.6478573	-0.8200737	-0.6415031	0.0368448
Selenocysteine synthesis	-0.6491215	-0.8080453	-0.6337621	-0.0075299
Eukaryotic Translation Termination	-0.6569639	-0.7940136	-0.6408712	0.0066794
L13a-mediated translational silencing of Ceruloplasmin expression	-0.6233883	-0.8017335	-0.5842985	0.0441376
GTP hydrolysis and joining of the 60S ribosomal subunit	-0.6202016	-0.7993446	-0.5855189	0.0503406
Cap-dependent Translation Initiation	-0.6142431	-0.8001803	-0.5834045	0.0418868
Eukaryotic Translation Initiation	-0.6142431	-0.8001803	-0.5834045	0.0418868
Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	-0.6441597	-0.7669569	-0.5896487	0.0245412
SRP-dependent cotranslational protein targeting to membrane	-0.6547855	-0.7527980	-0.5445330	0.0826122
Response of EIF2AK4 (GCN2) to amino acid deficiency	-0.6197982	-0.7547504	-0.5728307	0.0136216
Formation of ATP by chemiosmotic coupling	-0.8137677	-0.7152418	-0.2941399	0.1376132
Formation of the ternary complex, and subsequently, the 43S complex	-0.5757280	-0.7819123	-0.5725333	0.0777060
CD163 mediating an anti-inflammatory response	0.0480724	0.2985903	0.7613056	0.7644081
Mitochondrial translation initiation	-0.6774710	-0.6964576	-0.4755113	0.0641177
Mitochondrial translation elongation	-0.6894691	-0.6802258	-0.4692247	0.0584985
SARS-CoV-2 modulates host translation machinery	-0.5956896	-0.6889052	-0.5654447	0.0063056
Mitochondrial translation termination	-0.6604095	-0.6820556	-0.4651817	0.0643845
Ribosomal scanning and start codon recognition	-0.5604434	-0.7322003	-0.4964772	0.1035441
Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	-0.5544258	-0.7359996	-0.4952984	0.0933857
Translation initiation complex formation	-0.5512197	-0.7315119	-0.4969251	0.1005156
Mitochondrial translation	-0.6410081	-0.6716403	-0.4664192	0.0619103
Selenoamino acid metabolism	-0.5591625	-0.6956466	-0.5290464	0.0233945
Folding of actin by CCT/TriC	-0.5636091	-0.5241712	-0.5602801	0.3065442
Nonsense Mediated Decay (NMD) enhanced by the Exon Junction Complex (EJC)	-0.5284602	-0.6619947	-0.5282181	0.0414159
Nonsense-Mediated Decay (NMD)	-0.5284602	-0.6619947	-0.5282181	0.0414159
Regulation of expression of SLITs and ROBOs	-0.5355502	-0.6597398	-0.5008610	0.1047330
Phosphate bond hydrolysis by NUDT proteins	-0.5383516	-0.7730733	-0.0518890	0.2935613
Translation	-0.6010691	-0.6187902	-0.4696772	0.0594560
LTC4-CYSLTR mediated IL4 production	0.2796581	-0.5652996	-0.3885787	-0.6465763
Vpu mediated degradation of CD4	-0.4668044	-0.6472094	-0.4826234	0.2852529
RUNX1 and FOXP3 control the development of regulatory T lymphocytes (Tregs)	0.0383103	0.6761356	0.5626497	0.3958365
Vif-mediated degradation of APOBEC3G	-0.5064436	-0.6276950	-0.4230182	0.3191525
Complex III assembly	-0.6616507	-0.6002002	-0.3216513	-0.0227442
Classical antibody-mediated complement activation	-0.5773324	0.2385205	0.5380136	-0.4676725
Scavenging of heme from plasma	-0.5418474	0.2753666	0.5710768	-0.4449581
Regulation of activated PAK-2p34 by proteasome mediated degradation	-0.4718913	-0.6079543	-0.4271530	0.3355895
Cristae formation	-0.6654665	-0.5625360	-0.3297465	0.1157547
Ubiquitin Mediated Degradation of Phosphorylated Cdc25A	-0.5150297	-0.6186750	-0.4133062	0.2479403
p53-Independent DNA Damage Response	-0.5150297	-0.6186750	-0.4133062	0.2479403
p53-Independent G1/S DNA damage checkpoint	-0.5150297	-0.6186750	-0.4133062	0.2479403
FBXL7 down-regulates AURKA during mitotic entry and in early mitosis	-0.5077209	-0.5917372	-0.4278034	0.2883532
CD22 mediated BCR regulation	-0.5355680	0.2844132	0.5790498	-0.3920388
Ubiquitin-dependent degradation of Cyclin D	-0.4774111	-0.5935571	-0.4425109	0.2835855
Autodegradation of the E3 ubiquitin ligase COP1	-0.4821322	-0.5750769	-0.4620775	0.2750090
Influenza Viral RNA Transcription and Replication	-0.5122149	-0.5761048	-0.4965321	-0.0534557

#mitch_report(res=mm2,outfile="multireactomestratified_eos_mitchreport.html",overwrite=TRUE)

l2 <- list("crp_pod1_a"=crp_pod1_a_adj, "crp pod1 b"=crp_pod1_b_adj,
  "dex crplo pod1"=dex_crplo_pod1_adj, "dex crphi pod1"=dex_crphi_pod1_adj)
m2 <- mitch_import(x=l2, DEtype="deseq2", geneTable=gt )

## Note: Mean no. genes in input = 21313

## Note: no. genes in output = 21253

## Note: estimated proportion of input genes in output = 0.997

mm2 <- mitch_calc(x=m2,genesets=reactome,minsetsize=5,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be 
##             statistically significant.

top <- head(subset (mm2$enrichment_result,p.adjustMANOVA<0.01),50)
top <- top[,c(1,4:7)]
rownames(top) <- top[,1]
top[,1] = NULL
colnames(top) <- gsub("^s\\.","",colnames(top))
colfunc <- colorRampPalette(c("blue", "white", "red"))
heatmap.2(as.matrix(top),trace="none",col=colfunc(25),scale="none",
    margins = c(7,20), cexRow=0.6, cexCol=0.7 )

as.matrix(top) |>
  kbl(caption="Top REACTOMEs in multi enrichment analysis stratified POD1") |>
  kable_paper("hover", full_width = F)

Top REACTOMEs in multi enrichment analysis stratified POD1

	crp_pod1_a	crp.pod1.b	dex.crplo.pod1	dex.crphi.pod1
Establishment of Sister Chromatid Cohesion	0.6802647	-0.4141024	-0.7731595	-0.1288870
CD163 mediating an anti-inflammatory response	0.8177689	0.6035067	0.2168981	0.3802659
Cohesin Loading onto Chromatin	0.7607683	-0.4192252	-0.6719484	0.0912677
Defects of platelet adhesion to exposed collagen	0.0179163	0.6446557	0.7465995	-0.4375206
Insulin-like Growth Factor-2 mRNA Binding Proteins (IGF2BPs/IMPs/VICKZs) bind RNA	0.7189564	0.5092641	-0.4002134	-0.4583235
G2/M DNA replication checkpoint	0.3611069	0.5359563	-0.3616152	-0.7507718
Defective binding of VWF variant to GPIb:IX:V	0.1991340	0.5923193	0.7482116	-0.3912462
Enhanced binding of GP1BA variant to VWF multimer:collagen	0.1991340	0.5923193	0.7482116	-0.3912462
CD22 mediated BCR regulation	-0.3651203	0.5163091	0.1233814	-0.8108614
Erythrocytes take up oxygen and release carbon dioxide	0.5902422	0.8004330	-0.0507659	-0.2809941
Phosphorylation of Emi1	-0.1619366	0.6310224	-0.0675076	-0.7816005
Scavenging of heme from plasma	-0.2924731	0.4724193	0.1140335	-0.7763233
NFE2L2 regulates pentose phosphate pathway genes	0.7738762	0.4843257	0.2343375	0.1040598
Classical antibody-mediated complement activation	-0.2969975	0.4468521	0.1261972	-0.7520661
Type I hemidesmosome assembly	0.1200988	0.5509885	0.0846317	-0.7228054
FCGR activation	-0.2529432	0.3941056	0.0198179	-0.7704262
Fructose metabolism	-0.4634688	-0.3649225	0.6109251	0.2831323
Creation of C4 and C2 activators	-0.2940033	0.4135334	0.1299496	-0.7183099
Neurotransmitter clearance	0.2082647	0.0614518	0.6183147	0.5651621
Common Pathway of Fibrin Clot Formation	0.2776546	0.4569535	0.1834347	-0.5754020
Initial triggering of complement	-0.2783734	0.3783444	0.1360936	-0.6400733
Unwinding of DNA	-0.3673164	0.2302230	-0.0271488	-0.6684557
Mitotic Telophase/Cytokinesis	0.5578227	-0.1762639	-0.5239678	-0.1138998
Regulation of IFNG signaling	0.5575525	-0.0247187	-0.5526827	0.0013654
Role of LAT2/NTAL/LAB on calcium mobilization	-0.2017832	0.3194943	0.0128509	-0.6841241
STAT5 activation downstream of FLT3 ITD mutants	0.5945208	0.4826252	-0.0124061	0.1456516
MET activates RAP1 and RAC1	0.6576284	-0.1930236	-0.3387375	0.1341618
Maturation of protein 3a_9683673	0.1829013	0.3807611	-0.2558526	-0.5932132
Maturation of protein 3a_9694719	0.1829013	0.3807611	-0.2558526	-0.5932132
Maturation of hRSV A proteins	0.5255758	-0.3835217	-0.3965450	0.1109445
Protein repair	0.4695251	0.1666431	0.0329458	-0.5619774
Microtubule-dependent trafficking of connexons from Golgi to the plasma membrane	0.2936302	0.5563690	0.2653516	-0.3115437
Transport of connexons to the plasma membrane	0.2936302	0.5563690	0.2653516	-0.3115437
Butyrophilin (BTN) family interactions	-0.4953161	-0.2848091	0.4091889	0.2622605
Binding and Uptake of Ligands by Scavenger Receptors	-0.1384618	0.4153255	0.0833383	-0.5895184
Regulation of IFNA/IFNB signaling	0.2271393	0.2304976	-0.4334149	-0.5024246
Role of phospholipids in phagocytosis	-0.2201286	0.3277227	0.0336780	-0.6219713
Antigen activates B Cell Receptor (BCR) leading to generation of second messengers	-0.1577067	0.3608949	0.0157600	-0.6230321
FCGR3A-mediated IL10 synthesis	-0.1517052	0.3427544	0.0317556	-0.6235094
Respiratory syncytial virus (RSV) genome replication, transcription and translation	0.5044498	-0.3303492	-0.3850650	0.0161334
Termination of O-glycan biosynthesis	0.0940390	0.5751640	0.0588693	-0.4005964
FASTK family proteins regulate processing and stability of mitochondrial RNAs	0.4030130	-0.3589576	-0.0805164	0.4435934
Processing and activation of SUMO	0.0273219	-0.5267712	-0.3714447	-0.2779457
FCERI mediated Ca+2 mobilization	-0.1481838	0.2691847	-0.0170248	-0.6254893
Platelet sensitization by LDL	0.5657638	0.1449887	-0.2630492	-0.2541319
Diseases of hemostasis	0.0380269	0.4008982	0.4307982	-0.3551282
N-Glycan antennae elongation	0.2076644	0.3585519	-0.2396387	-0.4764371
Regulation of Complement cascade	-0.1708103	0.3860799	0.0986701	-0.5130640
Translocation of ZAP-70 to Immunological synapse	-0.4939627	-0.2189850	0.0871332	-0.3716418
Signaling by PDGFR in disease	0.4310614	-0.2670989	-0.4109943	-0.0501926

#mitch_report(res=mm2,outfile="multireactomestratified_pod1_mitchreport.html",overwrite=TRUE)

Session information

For reproducibility

sessionInfo()

## R version 4.5.2 (2025-10-31)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.4 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8          LC_NUMERIC=C                 
##  [3] LC_TIME=en_US.UTF-8           LC_COLLATE=en_US.UTF-8       
##  [5] LC_MONETARY=en_US.UTF-8       LC_MESSAGES=en_US.UTF-8      
##  [7] LC_PAPER=en_US.UTF-8          LC_NAME=en_US.UTF-8          
##  [9] LC_ADDRESS=en_US.UTF-8        LC_TELEPHONE=en_US.UTF-8     
## [11] LC_MEASUREMENT=en_US.UTF-8    LC_IDENTIFICATION=en_US.UTF-8
## 
## time zone: Etc/UTC
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats4    stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] gtools_3.9.5                RhpcBLASctl_0.23-42        
##  [3] xlsx_0.6.5                  DT_0.34.0                  
##  [5] eulerr_7.1.0                ggplot2_4.0.3              
##  [7] kableExtra_1.4.0            MASS_7.3-65                
##  [9] mitch_1.22.1                DESeq2_1.50.2              
## [11] SummarizedExperiment_1.40.0 Biobase_2.70.0             
## [13] MatrixGenerics_1.22.0       matrixStats_1.5.0          
## [15] GenomicRanges_1.62.1        Seqinfo_1.0.0              
## [17] IRanges_2.44.0              S4Vectors_0.48.1           
## [19] BiocGenerics_0.56.0         generics_0.1.4             
## [21] dplyr_1.2.1                 WGCNA_1.74                 
## [23] fastcluster_1.3.0           dynamicTreeCut_1.63-1      
## [25] reshape2_1.4.5              gplots_3.3.0               
## 
## loaded via a namespace (and not attached):
##   [1] RColorBrewer_1.1-3    rstudioapi_0.17.1     jsonlite_2.0.0       
##   [4] magrittr_2.0.4        farver_2.1.2          rmarkdown_2.30       
##   [7] vctrs_0.7.3           base64enc_0.1-3       htmltools_0.5.8.1    
##  [10] S4Arrays_1.10.1       progress_1.2.3        SparseArray_1.10.10  
##  [13] Formula_1.2-5         sass_0.4.10           KernSmooth_2.23-26   
##  [16] bslib_0.9.0           htmlwidgets_1.6.4     plyr_1.8.9           
##  [19] echarts4r_0.5.0       impute_1.84.0         cachem_1.1.0         
##  [22] mime_0.13             lifecycle_1.0.5       iterators_1.0.14     
##  [25] pkgconfig_2.0.3       Matrix_1.7-4          R6_2.6.1             
##  [28] fastmap_1.2.0         shiny_1.11.1          digest_0.6.39        
##  [31] colorspace_2.1-2      GGally_2.4.0          textshaping_1.0.4    
##  [34] Hmisc_5.2-5           labeling_0.4.3        polyclip_1.10-7      
##  [37] abind_1.4-8           compiler_4.5.2        withr_3.0.2          
##  [40] doParallel_1.0.17     htmlTable_2.5.0       S7_0.2.2             
##  [43] backports_1.5.1       BiocParallel_1.44.0   ggstats_0.13.0       
##  [46] DelayedArray_0.36.1   caTools_1.18.3        tools_4.5.2          
##  [49] foreign_0.8-90        otel_0.2.0            beeswarm_0.4.0       
##  [52] httpuv_1.6.16         nnet_7.3-20           glue_1.8.0           
##  [55] promises_1.5.0        grid_4.5.2            polylabelr_1.0.0     
##  [58] checkmate_2.3.4       cluster_2.1.8.1       gtable_0.3.6         
##  [61] preprocessCore_1.72.0 tidyr_1.3.2           hms_1.1.4            
##  [64] data.table_1.18.4     xml2_1.5.1            XVector_0.50.0       
##  [67] foreach_1.5.2         pillar_1.11.1         stringr_1.6.0        
##  [70] later_1.4.4           rJava_1.0-18          splines_4.5.2        
##  [73] lattice_0.22-7        survival_3.8-3        tidyselect_1.2.1     
##  [76] locfit_1.5-9.12       knitr_1.50            gridExtra_2.3        
##  [79] svglite_2.2.2         xfun_0.54             stringi_1.8.7        
##  [82] statnet.common_4.13.0 yaml_2.3.11           evaluate_1.0.5       
##  [85] codetools_0.2-20      xlsxjars_0.9.0        tibble_3.3.0         
##  [88] cli_3.6.5             rpart_4.1.24          xtable_1.8-4         
##  [91] systemfonts_1.3.1     jquerylib_0.1.4       network_1.20.0       
##  [94] Rcpp_1.1.1-1.1        coda_0.19-4.1         parallel_4.5.2       
##  [97] prettyunits_1.2.0     bitops_1.0-9          viridisLite_0.4.3    
## [100] scales_1.4.0          purrr_1.2.0           crayon_1.5.3         
## [103] rlang_1.2.0