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)

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<0.05),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

crp_t0_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
1140	Phosphate bond hydrolysis by NTPDase proteins	5	0.0059553	-0.7101669	0.0428206
1492	SUMO is proteolytically processed	6	0.0058929	-0.6491188	0.0425305
1141	Phosphate bond hydrolysis by NUDT proteins	7	0.0065774	-0.5930894	0.0462578
979	NOTCH4 Activation and Transmission of Signal to the Nucleus	10	0.0012732	-0.5883440	0.0145040
1361	Regulation of NFE2L2 gene expression	8	0.0042839	0.5831580	0.0342802
1633	Small interfering RNA (siRNA) biogenesis	9	0.0033815	-0.5641147	0.0289609
155	Beta-oxidation of pristanoyl-CoA	9	0.0045002	-0.5468033	0.0352517
317	Cytochrome c-mediated apoptotic response	13	0.0006671	-0.5450005	0.0088814
1186	Processing and activation of SUMO	10	0.0036639	-0.5306130	0.0303662
26	ATF6 (ATF6-alpha) activates chaperones	12	0.0020616	-0.5136487	0.0202694
111	Apoptosis induced DNA fragmentation	10	0.0057719	-0.5040897	0.0419632
558	Formation of apoptosome	11	0.0047614	-0.4914847	0.0364093
1411	Regulation of the apoptosome activity	11	0.0047614	-0.4914847	0.0364093
851	MAPK3 (ERK1) activation	10	0.0073218	-0.4897347	0.0496801
87	Advanced glycosylation endproduct receptor signaling	12	0.0036717	-0.4842926	0.0303662
1358	Regulation of MITF-M-dependent genes involved in lysosome biogenesis and autophagy	16	0.0008086	-0.4836472	0.0103196
454	ER Quality Control Compartment (ERQC)	21	0.0001924	-0.4699681	0.0034007
104	Antigen Presentation: Folding, assembly and peptide loading of class I MHC	30	0.0000104	-0.4649512	0.0003645
411	Diseases of branched-chain amino acid catabolism	13	0.0039261	-0.4619362	0.0317879
989	NRIF signals cell death from the nucleus	15	0.0023776	-0.4530863	0.0225696
217	Calnexin/calreticulin cycle	26	0.0000695	-0.4506184	0.0015401
958	N-glycan trimming in the ER and Calnexin/Calreticulin cycle	35	0.0000052	-0.4448389	0.0002190
730	Incretin synthesis, secretion, and inactivation	14	0.0045889	-0.4375065	0.0355135
1692	Synthesis, secretion, and inactivation of Glucagon-like Peptide-1 (GLP-1)	14	0.0045889	-0.4375065	0.0355135
1161	Platelet sensitization by LDL	16	0.0029610	-0.4290748	0.0265387
715	IRAK4 deficiency (TLR2/4)	15	0.0050630	-0.4179761	0.0381109
924	Mitochondrial calcium ion transport	22	0.0010352	-0.4040145	0.0123897
1375	Regulation of TLR by endogenous ligand	15	0.0071826	-0.4008694	0.0491079
661	Golgi Associated Vesicle Biogenesis	55	0.0000010	-0.3805880	0.0000590
657	Glycosphingolipid catabolism	31	0.0004121	-0.3664988	0.0061972

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/Rtmppyg3bi/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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb94599fc09.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
1493	SUMO is conjugated to E1 (UBA2:SAE1)	5	0.0039853	-0.7434937	0.0156817
119	Arachidonate production from DAG	5	0.0040971	-0.7412385	0.0160237
1802	Translation	293	0.0000000	-0.7315663	0.0000000
1460	SARS-CoV-2 modulates host translation machinery	49	0.0000000	-0.7302310	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/Rtmppyg3bi/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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb97ddf3581.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
1430	Response to metal ions	6	0.0010266	0.7738975	0.0102715
736	Inhibition of Signaling by Overexpressed EGFR	5	0.0035418	0.7530497	0.0269992
1597	Signaling by Overexpressed Wild-Type EGFR in Cancer	5	0.0035418	0.7530497	0.0269992
569	Formation of xylulose-5-phosphate	5	0.0052750	-0.7203690	0.0359118
962	NFE2L2 regulates pentose phosphate pathway genes	8	0.0005941	0.7010944	0.0065974
596	G2/M DNA replication checkpoint	5	0.0073992	0.6916039	0.0448704
554	Formation of a pool of free 40S subunits	100	0.0000000	-0.6857997	0.0000000
1120	Peptide chain elongation	88	0.0000000	-0.6830724	0.0000000
490	Eukaryotic Translation Elongation	93	0.0000000	-0.6712259	0.0000000
1507	Selenocysteine synthesis	92	0.0000000	-0.6661188	0.0000000
1856	Viral mRNA Translation	88	0.0000000	-0.6576198	0.0000000
1447	SARS-CoV-1 modulates host translation machinery	36	0.0000000	-0.6564783	0.0000000
444	EGFR interacts with phospholipase C-gamma	6	0.0054930	0.6545238	0.0363862
492	Eukaryotic Translation Termination	92	0.0000000	-0.6545152	0.0000000
567	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0000000	-0.6435519	0.0000000
809	L13a-mediated translational silencing of Ceruloplasmin expression	110	0.0000000	-0.6423239	0.0000000
1909	rRNA modification in the mitochondrion	8	0.0017421	-0.6391975	0.0156382
1033	Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	94	0.0000000	-0.6370409	0.0000000
1679	Synthesis of diphthamide-EEF2	8	0.0018132	-0.6367969	0.0159180
613	GTP hydrolysis and joining of the 60S ribosomal subunit	111	0.0000000	-0.6301568	0.0000000
216	Cap-dependent Translation Initiation	118	0.0000000	-0.6262718	0.0000000
491	Eukaryotic Translation Initiation	118	0.0000000	-0.6262718	0.0000000
479	Erythrocytes take up oxygen and release carbon dioxide	7	0.0049225	0.6137222	0.0347652
72	Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	59	0.0000000	-0.5977723	0.0000000
1793	Translation initiation complex formation	58	0.0000000	-0.5923762	0.0000000
1483	STAT5 activation downstream of FLT3 ITD mutants	9	0.0021701	0.5901274	0.0181255
1356	Regulation of NFE2L2 gene expression	8	0.0038459	0.5901153	0.0287469
1426	Response of EIF2AK4 (GCN2) to amino acid deficiency	100	0.0000000	-0.5868369	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/Rtmppyg3bi/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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb926dc754f.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
856	MECP2 regulates transcription of neuronal ligands	5	0.0033542	-0.7574205	0.0289845
984	NR1H2 & NR1H3 regulate gene expression to control bile acid homeostasis	7	0.0005220	-0.7570978	0.0075305
1148	Phosphorylation of Emi1	6	0.0017918	-0.7360959	0.0186012
969	NFE2L2 regulating inflammation associated genes	5	0.0046814	-0.7302904	0.0377353
777	Interleukin-21 signaling	9	0.0002255	-0.7099452	0.0042146
835	Loss of MECP2 binding ability to the NCoR/SMRT complex	7	0.0011803	-0.7078822	0.0140064
1105	POLB-Dependent Long Patch Base Excision Repair	8	0.0011699	-0.6626910	0.0140024
467	Eicosanoids	8	0.0018576	0.6353376	0.0190404
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
982	NR1H2 & NR1H3 regulate gene expression linked to lipogenesis	8	0.0034139	-0.5977152	0.0292701
1837	Type I hemidesmosome assembly	8	0.0034176	-0.5976466	0.0292701
987	NR1H3 & NR1H2 regulate gene expression linked to cholesterol transport and efflux	32	0.0000000	-0.5723853	0.0000017
787	Interleukin-9 signaling	8	0.0060785	-0.5601043	0.0455769
1192	Processive synthesis on the C-strand of the telomere	19	0.0000532	-0.5354085	0.0013319
61	Activation of PUMA and translocation to mitochondria	9	0.0056612	-0.5325618	0.0427870
1416	Removal of the Flap Intermediate from the C-strand	17	0.0001492	-0.5311991	0.0031371
775	Interleukin-2 signaling	11	0.0024922	-0.5265690	0.0234263
1845	Unwinding of DNA	12	0.0017431	-0.5219218	0.0183544
986	NR1H2 and NR1H3-mediated signaling	38	0.0000000	-0.5174201	0.0000024
673	HDMs demethylate histones	22	0.0000630	-0.4926954	0.0014995
1486	STAT3 nuclear events downstream of ALK signaling	11	0.0047408	-0.4917259	0.0377456
1724	TP53 Regulates Transcription of Genes Involved in G2 Cell Cycle Arrest	18	0.0003072	-0.4913051	0.0053096
1418	Repression of WNT target genes	14	0.0022957	-0.4706063	0.0221186
676	HDR through MMEJ (alt-NHEJ)	12	0.0051782	-0.4660689	0.0400736
1378	Regulation of TP53 Activity through Acetylation	29	0.0000154	-0.4636314	0.0004878
1292	RORA activates gene expression	18	0.0007845	-0.4571511	0.0100777

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/Rtmppyg3bi/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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb96594c3c.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),30)
mtop |> kbl(caption=paste(myname,"REACTOME")) |> kable_paper("hover", full_width = F)

dex_eos_adj REACTOME

	set	setSize	pANOVA	s.dist	p.adjustANOVA
573	Formation of the ureteric bud	5	0.0014238	0.8236428	0.0338956
180	CD163 mediating an anti-inflammatory response	9	0.0000937	0.7518468	0.0035494
1208	Protein repair	6	0.0016959	0.7399021	0.0380212
369	Defective binding of VWF variant to GPIb:IX:V	7	0.0009042	0.7242764	0.0239307
476	Enhanced binding of GP1BA variant to VWF multimer:collagen	7	0.0009042	0.7242764	0.0239307
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
1157	Platelet Adhesion to exposed collagen	16	0.0020778	0.4445367	0.0436758
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
1707	TGFBR3 expression	20	0.0013035	-0.4152464	0.0318770
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
1475	SIRT1 negatively regulates rRNA expression	22	0.0010710	0.4028282	0.0275902
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
1240	RHO GTPases activate IQGAPs	25	0.0012173	0.3737107	0.0305436

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/Rtmppyg3bi/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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb92ab63285.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
1021	Neurotransmitter clearance	6	0.0019558	0.7300011	0.0136127
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
23	ARMS-mediated activation	6	0.0041525	-0.6756719	0.0256495
596	G2/M DNA replication checkpoint	5	0.0089926	-0.6745670	0.0478526
774	Interleukin-21 signaling	9	0.0006451	-0.6567083	0.0055079
1430	Response to metal ions	6	0.0053518	-0.6565162	0.0320274
1201	Protein repair	6	0.0060969	-0.6464913	0.0351716
1474	SMAC (DIABLO) binds to IAPs	7	0.0033116	-0.6410350	0.0212759
1475	SMAC(DIABLO)-mediated dissociation of IAP:caspase complexes	7	0.0033116	-0.6410350	0.0212759
1476	SMAC, XIAP-regulated apoptotic response	7	0.0033116	-0.6410350	0.0212759
175	Butyrophilin (BTN) family interactions	10	0.0006208	0.6249306	0.0053480
874	Maturation of protein 3a_9683673	9	0.0014628	-0.6124605	0.0107667
875	Maturation of protein 3a_9694719	9	0.0014628	-0.6124605	0.0107667
1286	ROBO receptors bind AKAP5	7	0.0061922	-0.5974368	0.0355078
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
1831	Type I hemidesmosome assembly	8	0.0049171	-0.5741704	0.0296104
1306	RUNX3 regulates CDKN1A transcription	7	0.0093040	0.5675959	0.0491016
289	Condensation of Prometaphase Chromosomes	11	0.0011605	-0.5655862	0.0088828
939	Mitotic Telophase/Cytokinesis	13	0.0004214	-0.5647834	0.0037828
198	CREB1 phosphorylation through the activation of Adenylate Cyclase	9	0.0040305	-0.5535367	0.0252203
1058	OAS antiviral response	8	0.0080213	-0.5412568	0.0439003
278	Cohesin Loading onto Chromatin	10	0.0035870	-0.5318270	0.0228165
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
1357	Regulation of NPAS4 gene expression	11	0.0043090	-0.4970342	0.0264525

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/Rtmppyg3bi/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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb9865b580.html

## 
## Output created: /tmp/Rtmppyg3bi/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_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("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)

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("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)

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_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<0.05),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
Formation of xylulose-5-phosphate	-0.5645979	-0.5993342	-0.7188187	-0.0256908	-0.5512817	0.2090550
MECP2 regulates transcription of neuronal ligands	0.2891616	0.4716507	-0.1094498	-0.7555143	-0.7264660	-0.2341085
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
SUMO is conjugated to E1 (UBA2:SAE1)	-0.6691111	-0.7382603	-0.2370952	0.0034717	0.3656727	-0.4095211
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
Modulation by Mtb of host immune system	-0.4328656	-0.8225786	-0.3276983	0.1433056	0.4856463	-0.0329472
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
Phosphate bond hydrolysis by NUDT proteins	-0.5898896	-0.7452421	-0.4329879	0.2570477	0.2305758	0.0152675
Eukaryotic Translation Termination	-0.2201365	-0.8159854	-0.6516251	0.0855229	0.0029518	0.2416297
POLB-Dependent Long Patch Base Excision Repair	0.1600195	-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
Fructose metabolism	-0.2746730	-0.2257788	-0.5791812	0.1399898	-0.3878988	0.7030882
SRP-dependent cotranslational protein targeting to membrane	-0.3137107	-0.8098165	-0.5609328	0.0984679	0.1043269	0.0969541
RUNX1 regulates transcription of genes involved in BCR signaling	0.0000793	0.3429088	0.5935667	0.1495767	0.6900346	-0.3422429
Replacement of protamines by nucleosomes in the male pronucleus	-0.2815335	-0.6127973	0.2507929	0.2857358	0.6285284	-0.3005867
Activation of caspases through apoptosome-mediated cleavage	-0.5968166	-0.2860427	0.1480389	0.0998922	-0.0273947	-0.7806684
Phosphorylation of Emi1	0.2315229	-0.2472970	0.4386315	-0.7339167	0.0985922	-0.4531057
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	-0.4078749	0.5203898	-0.4513954
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
SUMO is transferred from E1 to E2 (UBE2I, UBC9)	-0.4931748	-0.6900561	-0.3916222	-0.0716630	0.2195821	-0.2664243
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
Activation of NIMA Kinases NEK9, NEK6, NEK7	0.0210837	-0.0371734	0.4603975	-0.4826159	0.1372584	-0.7083880
NR1H2 & NR1H3 regulate gene expression linked to triglyceride lipolysis in adipose	-0.0419175	0.1356446	-0.0841109	-0.6943549	-0.4581823	0.4916060

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

## Note: overwriting existing report

## Dataset saved as " /tmp/Rtmppyg3bi/multireactome_all_mitchreport.rds ".

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

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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                             
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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                             
## 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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb93d4b47ce.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
MECP2 regulates transcription of neuronal ligands	0.2836222	-0.7574205
Phosphorylation of Emi1	0.2254696	-0.7360959
NR1H2 & NR1H3 regulate gene expression to control bile acid homeostasis	-0.0547631	-0.7570978
Interleukin-21 signaling	0.2372312	-0.7099452
Loss of MECP2 binding ability to the NCoR/SMRT complex	0.1218432	-0.7078822
Phosphate bond hydrolysis by NTPDase proteins	-0.7101669	-0.0293528
NR1H2 & NR1H3 regulate gene expression linked to triglyceride lipolysis in adipose	-0.0498422	-0.6973062
POLB-Dependent Long Patch Base Excision Repair	0.1545833	-0.6626910
SUMO is proteolytically processed	-0.6491188	-0.0691700
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
Unwinding of DNA	0.3670510	-0.5219218
Type I hemidesmosome assembly	0.1770424	-0.5976466
NR1H2 & NR1H3 regulate gene expression linked to lipogenesis	-0.1419586	-0.5977152
Repression of WNT target genes	0.3720129	-0.4706063
NOTCH4 Activation and Transmission of Signal to the Nucleus	-0.5883440	0.0466880
Small interfering RNA (siRNA) biogenesis	-0.5641147	0.1233907
NR1H3 & NR1H2 regulate gene expression linked to cholesterol transport and efflux	-0.0718215	-0.5723853
Interleukin-2 signaling	0.2021842	-0.5265690
Beta-oxidation of pristanoyl-CoA	-0.5468033	0.1304861
TP53 Regulates Transcription of Genes Involved in G2 Cell Cycle Arrest	0.2702016	-0.4913051
Cytochrome c-mediated apoptotic response	-0.5450005	0.1278133
Formation of annular gap junctions	-0.3688655	-0.4207594
Synthesis of pyrophosphates in the cytosol	-0.4556765	-0.2980857
Processing and activation of SUMO	-0.5306130	-0.1210522
Processive synthesis on the C-strand of the telomere	0.0634320	-0.5354085
TGFBR3 regulates TGF-beta signaling	-0.2281356	-0.4855000
Glycosphingolipid transport	-0.4073092	-0.3441235
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
Regulation of MITF-M-dependent genes involved in lysosome biogenesis and autophagy	-0.4836472	0.1770786
Miscellaneous substrates	0.4991309	0.1048394
SARS-CoV-2 modulates autophagy	-0.3592571	-0.3609622
Antigen Presentation: Folding, assembly and peptide loading of class I MHC	-0.4649512	-0.2040842
Response of EIF2AK1 (HRI) to heme deficiency	-0.2431630	0.4425918
Advanced glycosylation endproduct receptor signaling	-0.4842926	0.1357093
HDMs demethylate histones	0.0890679	-0.4926954
MAPK3 (ERK1) activation	-0.4897347	-0.0998079
TGFBR3 PTM regulation	-0.4738975	-0.1511436
Fatty acids	0.3749085	0.3264683
MASTL Facilitates Mitotic Progression	-0.4835590	-0.0666972
ATF6 (ATF6-alpha) activates chaperone genes	-0.4698994	-0.1211985
Establishment of Sister Chromatid Cohesion	-0.4163669	-0.2386993
HSF1-dependent transactivation	0.2537515	-0.4033974

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

## Dataset saved as " /tmp/Rtmppyg3bi/multireactome_t0_mitchreport.rds ".

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

## 1/36                             
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## 9/36                             
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## 11/36                             
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## 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                             
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## 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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb93413dc41.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
Formation of the ureteric bud	-0.4916795	0.8236428
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
Protein repair	-0.4770912	0.7399021
MECP2 regulates transcription of neuronal ligands	0.4675457	-0.7329635
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
SUMO is conjugated to E1 (UBA2:SAE1)	-0.7434937	0.3562608
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
Post-transcriptional silencing by small RNAs	0.7119602	-0.3856857
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
Phosphate bond hydrolysis by NUDT proteins	-0.7494543	0.2234189
Mitochondrial translation	-0.7762502	0.0838403
Regulation of CDH11 mRNA translation by microRNAs	0.6300305	-0.4579828
Regulation of NPAS4 mRNA translation	0.6300305	-0.4579828
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
Arachidonate production from DAG	-0.7412385	0.1408020
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

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

## Dataset saved as " /tmp/Rtmppyg3bi/multireactome_eos_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]

## 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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb944954ebc.html

## 
## Output created: /tmp/Rtmppyg3bi/mitch_report.html

## [1] TRUE

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<0.05),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
Response to metal ions	0.7738975	-0.6565162
G2/M DNA replication checkpoint	0.6916039	-0.6745670
Fructose metabolism	-0.5808825	0.7032046
CD163 mediating an anti-inflammatory response	0.8726171	0.0578724
Butyrophilin (BTN) family interactions	-0.5751165	0.6249306
Activation of NIMA Kinases NEK9, NEK6, NEK7	0.4563683	-0.7084762
Regulation of IFNA/IFNB signaling	0.4407200	-0.6790484
Type I hemidesmosome assembly	0.5655331	-0.5741704
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	0.3437529	-0.6895345
Maturation of protein 3a_9683673	0.4537333	-0.6124605
Maturation of protein 3a_9694719	0.4537333	-0.6124605
Neurotransmitter clearance	-0.1916349	0.7300011
Synthesis of diphthamide-EEF2	-0.6367969	0.3932572
NFE2L2 regulates pentose phosphate pathway genes	0.7010944	-0.2182984
Formation of a pool of free 40S subunits	-0.6857997	0.2577601
Peptide chain elongation	-0.6830724	0.2626796
Interleukin-21 signaling	0.3205925	-0.6567083
Mitotic Telophase/Cytokinesis	0.4479502	-0.5647834
Eukaryotic Translation Elongation	-0.6712259	0.2539230
Selenocysteine synthesis	-0.6661188	0.2476449
SARS-CoV-1 modulates host translation machinery	-0.6564783	0.2660210
Viral mRNA Translation	-0.6576198	0.2320576
Eukaryotic Translation Termination	-0.6545152	0.2318601
EGFR interacts with phospholipase C-gamma	0.6545238	0.2238434
Platelet sensitization by LDL	0.4364847	-0.5274639
Interleukin-6 signaling	0.3320906	-0.5967801
Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	-0.6370409	0.2347927
L13a-mediated translational silencing of Ceruloplasmin expression	-0.6423239	0.2190624
Formation of the ternary complex, and subsequently, the 43S complex	-0.6435519	0.2150297
GTP hydrolysis and joining of the 60S ribosomal subunit	-0.6301568	0.2144120
Cap-dependent Translation Initiation	-0.6262718	0.2224529
Eukaryotic Translation Initiation	-0.6262718	0.2224529
Cohesin Loading onto Chromatin	0.3900202	-0.5318270
N-Glycan antennae elongation	0.4727963	-0.4595672
SMAC (DIABLO) binds to IAPs	0.0041151	-0.6410350
SMAC(DIABLO)-mediated dissociation of IAP:caspase complexes	0.0041151	-0.6410350
SMAC, XIAP-regulated apoptotic response	0.0041151	-0.6410350
Common Pathway of Fibrin Clot Formation	0.4487759	-0.4556207
rRNA modification in the mitochondrion	-0.6391975	-0.0022594
Regulation of TP53 Activity through Association with Co-factors	-0.2347836	0.5928991
Condensation of Prometaphase Chromosomes	0.2865763	-0.5655862
Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	-0.5977723	0.2064351
Translation initiation complex formation	-0.5923762	0.1939137
Regulation of IFNG signaling	0.3808627	-0.4926584
Response of EIF2AK4 (GCN2) to amino acid deficiency	-0.5868369	0.2047965
Interaction between L1 and Ankyrins	0.4903443	-0.3804806

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

## Dataset saved as " /tmp/Rtmppyg3bi/multireactome_pod1_mitchreport.rds ".

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

## 1/36                             
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## 3/36                             
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## 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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb97d6670f4.html

## 
## Output created: /tmp/Rtmppyg3bi/mitch_report.html

## [1] TRUE

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<0.05),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	-0.8061739	0.0000000
547	Formation of ATP by chemiosmotic coupling	20	0.0000000	-0.7990801	0.0000000
492	Eukaryotic Translation Elongation	92	0.0000000	-0.7971237	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	-0.7859556	0.0000000
494	Eukaryotic Translation Termination	91	0.0000000	-0.7823329	0.0000000
659	Glycosphingolipid transport	7	0.0004070	-0.7715645	0.0020372
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	-0.7653675	0.0000000
1647	Sulfide oxidation to sulfate	5	0.0032844	-0.7591036	0.0120784
1485	SRP-dependent cotranslational protein targeting to membrane	110	0.0000000	-0.7565191	0.0000000
812	L13a-mediated translational silencing of Ceruloplasmin expression	109	0.0000000	-0.7511557	0.0000000
557	Formation of annular gap junctions	10	0.0000428	-0.7471180	0.0002570
616	GTP hydrolysis and joining of the 60S ribosomal subunit	110	0.0000000	-0.7368616	0.0000000
150	Beta oxidation of hexanoyl-CoA to butanoyl-CoA	5	0.0048349	-0.7276195	0.0163455
1141	Phosphate bond hydrolysis by NUDT proteins	7	0.0009235	-0.7229893	0.0040817
218	Cap-dependent Translation Initiation	117	0.0000000	-0.7220008	0.0000000
493	Eukaryotic Translation Initiation	117	0.0000000	-0.7220008	0.0000000
1431	Response of EIF2AK4 (GCN2) to amino acid deficiency	99	0.0000000	-0.7211906	0.0000000
569	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0000000	-0.7012300	0.0000000
72	Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	59	0.0000000	-0.6829061	0.0000000
1799	Translation initiation complex formation	58	0.0000000	-0.6788465	0.0000000
1443	Ribosomal scanning and start codon recognition	58	0.0000000	-0.6711633	0.0000000
1491	SUMO is conjugated to E1 (UBA2:SAE1)	5	0.0095891	-0.6688772	0.0286040
577	Fructose metabolism	7	0.0022264	-0.6674355	0.0087917
1511	Selenoamino acid metabolism	114	0.0000000	-0.6654668	0.0000000
1185	Prevention of phagosomal-lysosomal fusion	9	0.0005887	-0.6614875	0.0027806

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)

## Dataset saved as " /tmp/Rtmppyg3bi/crp_t0_a_adj_mitchreport.rds ".

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

## 1/36                             
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## 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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb915a7c88c.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
487	Establishment of Sister Chromatid Cohesion	11	0.0000674	-0.6938228	0.0108270
280	Cohesin Loading onto Chromatin	10	0.0002115	-0.6764959	0.0271735
1675	Synthesis of PIPs at the late endosome membrane	11	0.0003485	-0.6226559	0.0317686
1674	Synthesis of PIPs at the early endosome membrane	16	0.0000300	-0.6025613	0.0082662
1625	Signaling by cytosolic FGFR1 fusion mutants	18	0.0006981	-0.4615189	0.0343875
724	Impaired BRCA2 binding to PALB2	24	0.0002600	-0.4306090	0.0294743
511	FGFR1 mutant receptor activation	25	0.0007138	-0.3909709	0.0343875
359	Defective HDR through Homologous Recombination Repair (HRR) due to PALB2 loss of BRCA1 binding function	25	0.0008236	-0.3864115	0.0345009
360	Defective HDR through Homologous Recombination Repair (HRR) due to PALB2 loss of BRCA2/RAD51/RAD51C binding function	25	0.0008236	-0.3864115	0.0345009
369	Defective homologous recombination repair (HRR) due to BRCA1 loss of function	25	0.0008236	-0.3864115	0.0345009
371	Defective homologous recombination repair (HRR) due to PALB2 loss of function	25	0.0008236	-0.3864115	0.0345009
1560	Signaling by FGFR1 in disease	32	0.0001902	-0.3810989	0.0271735
1818	Transport of Ribonucleoproteins into the Host Nucleus	32	0.0013716	-0.3268757	0.0489456
725	Impaired BRCA2 binding to RAD51	35	0.0011144	-0.3183709	0.0421069
1184	Presynaptic phase of homologous DNA pairing and strand exchange	40	0.0005814	-0.3143060	0.0343875
180	CD22 mediated BCR regulation	59	0.0000360	0.3109324	0.0082662
370	Defective homologous recombination repair (HRR) due to BRCA2 loss of function	41	0.0006270	-0.3086060	0.0343875
407	Diseases of DNA Double-Strand Break Repair	41	0.0006270	-0.3086060	0.0343875
990	NS1 Mediated Effects on Host Pathways	40	0.0007563	-0.3077439	0.0345009
1676	Synthesis of PIPs at the plasma membrane	52	0.0002069	-0.2973974	0.0271735
700	Homologous DNA Pairing and Strand Exchange	43	0.0007506	-0.2970175	0.0345009
720	ISG15 antiviral mechanism	72	0.0000229	-0.2885560	0.0082662
1508	Scavenging of heme from plasma	71	0.0000487	0.2787277	0.0085298
661	Golgi Associated Vesicle Biogenesis	55	0.0004046	-0.2756844	0.0324844
408	Diseases of DNA repair	51	0.0013379	-0.2596163	0.0486439
273	Classical antibody-mediated complement activation	70	0.0004822	0.2412294	0.0343875
742	Initial triggering of complement	80	0.0002498	0.2368231	0.0294743
307	Creation of C4 and C2 activators	72	0.0006847	0.2314063	0.0343875
598	G2/M DNA damage checkpoint	66	0.0012625	-0.2294783	0.0467855
1381	Regulation of TP53 Activity through Phosphorylation	88	0.0003951	-0.2184988	0.0324844

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)

## Dataset saved as " /tmp/Rtmppyg3bi/crp_t0_b_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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## 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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb93ec2168c.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
119	Arachidonate production from DAG	5	0.0015498	-0.8172956	0.0107706
550	Formation of ATP by chemiosmotic coupling	20	0.0000000	-0.8137677	0.0000000
860	MET activates PI3K/AKT signaling	5	0.0026253	0.7768482	0.0168986
1093	PI3K events in ERBB4 signaling	6	0.0015335	0.7468285	0.0106955
873	Malate-aspartate shuttle	8	0.0004343	-0.7182484	0.0036798
1014	Negative regulation of activity of TFAP2 (AP-2) family transcription factors	6	0.0023559	-0.7168948	0.0153771
1669	Synthesis of Ketone Bodies	6	0.0027728	-0.7052547	0.0176216
1213	Purine ribonucleoside monophosphate biosynthesis	9	0.0003046	-0.6950836	0.0026736
882	Maturation of spike protein_9683686	5	0.0071580	-0.6944621	0.0385216
811	Ketone body metabolism	8	0.0007268	-0.6898618	0.0057788
933	Mitochondrial translation elongation	90	0.0000000	-0.6894701	0.0000000
1127	Peptide chain elongation	88	0.0000000	-0.6817694	0.0000000
934	Mitochondrial translation initiation	90	0.0000000	-0.6774720	0.0000000
1867	Viral mRNA Translation	88	0.0000000	-0.6691139	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	-0.6604115	0.0000000
497	Eukaryotic Translation Termination	92	0.0000000	-0.6569629	0.0000000
1487	SRP-dependent cotranslational protein targeting to membrane	111	0.0000000	-0.6547847	0.0000000
559	Formation of a pool of free 40S subunits	100	0.0000000	-0.6511768	0.0000000
1514	Selenocysteine synthesis	92	0.0000000	-0.6491205	0.0000000
1454	SARS-CoV-1 modulates host translation machinery	36	0.0000000	-0.6478547	0.0000000
1666	Synthesis of GDP-mannose	6	0.0060182	-0.6474939	0.0330316
1039	Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	94	0.0000000	-0.6441588	0.0000000
932	Mitochondrial translation	96	0.0000000	-0.6410100	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	-0.6233874	0.0000000
1415	Release of apoptotic factors from the mitochondria	6	0.0084707	-0.6206066	0.0441421

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)

## Dataset saved as " /tmp/Rtmppyg3bi/crp_eos_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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb91039dd98.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
1891	Zygotic genome activation (ZGA)	5	0.0048478	0.7273984	0.0269138
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
1304	RUNX1 regulates transcription of genes involved in WNT signaling	5	0.0072706	0.6931163	0.0364851
1460	SARS-CoV-2 modulates host translation machinery	49	0.0000000	-0.6889052	0.0000000
1333	Reelin signalling pathway	5	0.0082368	0.6822770	0.0393897
935	Mitochondrial translation termination	90	0.0000000	-0.6820556	0.0000000
933	Mitochondrial translation elongation	90	0.0000000	-0.6802258	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)

## Dataset saved as " /tmp/Rtmppyg3bi/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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb97a1d2f5c.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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	0.0013901	0.8254330	0.0087839
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	0.7607588	0.0004197
749	Insulin-like Growth Factor-2 mRNA Binding Proteins (IGF2BPs/IMPs/VICKZs) bind RNA	6	0.0022884	0.7189564	0.0132014
484	Establishment of Sister Chromatid Cohesion	11	0.0000933	0.6802647	0.0009437
1501	Scavenging by Class A Receptors	10	0.0003151	0.6578261	0.0025648
856	MET activates RAP1 and RAC1	10	0.0003164	0.6576284	0.0025648
1296	RUNX1 regulates transcription of genes involved in BCR signaling	6	0.0069065	0.6367801	0.0320467
25	ATF6 (ATF6-alpha) activates chaperone genes	10	0.0007206	0.6174928	0.0049796
614	Gain-of-function MRAS complexes activate RAF signaling	8	0.0028700	0.6086491	0.0157519
1467	SHOC2 M1731 mutant abolishes MRAS complex function	8	0.0028700	0.6086491	0.0157519
1578	Signaling by MRAS-complex mutants	8	0.0028700	0.6086491	0.0157519
21	APEX1-Independent Resolution of AP Sites via the Single Nucleotide Replacement Pathway	7	0.0053812	-0.6074421	0.0259732
480	Erythropoietin activates Phosphoinositide-3-kinase (PI3K)	11	0.0006336	0.5948935	0.0044588
1483	STAT5 activation downstream of FLT3 ITD mutants	9	0.0020101	0.5945208	0.0120295
307	Cross-presentation of particulate exogenous antigens (phagosomes)	8	0.0037787	0.5912450	0.0196187
479	Erythrocytes take up oxygen and release carbon dioxide	7	0.0068416	0.5902422	0.0318508
1390	Regulation of gene expression by Hypoxia-inducible Factor	8	0.0045948	0.5786067	0.0226904
1563	Signaling by FLT3 ITD and TKD mutants	15	0.0001385	0.5682205	0.0012916
442	EGFR Transactivation by Gastrin	7	0.0095201	0.5658746	0.0414698
1156	Platelet sensitization by LDL	16	0.0000890	0.5657579	0.0009195
1299	RUNX1 regulates transcription of genes involved in differentiation of keratinocytes	7	0.0104153	0.5590968	0.0442649
939	Mitotic Telophase/Cytokinesis	13	0.0004962	0.5578154	0.0036108
1347	Regulation of IFNG signaling	14	0.0003033	0.5575525	0.0025002
1083	PI-3K cascade:FGFR3	10	0.0030984	0.5401215	0.0166724
598	GAB1 signalosome	14	0.0005681	0.5319258	0.0041025
871	Maturation of hRSV A proteins	13	0.0010328	0.5255758	0.0068178
419	Displacement of DNA glycosylase by APEX1	9	0.0064262	-0.5245612	0.0304060
1066	Organic cation transport	8	0.0103885	0.5231819	0.0442490

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)

## Dataset saved as " /tmp/Rtmppyg3bi/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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb9f0d9989.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
165	Biosynthesis of Lipoxins (LX)	6	0.0018914	0.7323387	0.0194295
1192	Propionyl-CoA catabolism	5	0.0052667	-0.7205008	0.0432318
375	Defects of platelet adhesion to exposed collagen	6	0.0062430	0.6446557	0.0491511
356	Defective GALNT3 causes HFTC	8	0.0022068	0.6248882	0.0217394
178	CD163 mediating an anti-inflammatory response	8	0.0031152	0.6035067	0.0279636
355	Defective GALNT12 causes CRCS1	8	0.0036114	0.5941398	0.0316781
1739	Termination of O-glycan biosynthesis	15	0.0001146	0.5751640	0.0019143
910	Microtubule-dependent trafficking of connexons from Golgi to the plasma membrane	12	0.0008453	0.5563690	0.0108478
1814	Transport of connexons to the plasma membrane	12	0.0008453	0.5563690	0.0108478
1181	Processing and activation of SUMO	10	0.0039181	-0.5267712	0.0340172
180	CD22 mediated BCR regulation	58	0.0000000	0.5163091	0.0000000
408	Diseases of branched-chain amino acid catabolism	13	0.0013233	-0.5142764	0.0148661
1413	Repression of WNT target genes	14	0.0008922	0.5128033	0.0112756
1670	Synthesis of PIPs at the late endosome membrane	11	0.0038892	-0.5026748	0.0339596
1661	Synthesis of Leukotrienes (LT) and Eoxins (EX)	15	0.0009140	0.4944219	0.0113753
1503	Scavenging of heme from plasma	70	0.0000000	0.4724193	0.0000000
618	Gap junction assembly	16	0.0013967	0.4613528	0.0153559
283	Common Pathway of Fibrin Clot Formation	13	0.0043321	0.4569535	0.0365247
1149	Plasma lipoprotein remodeling	18	0.0008470	0.4542605	0.0108478
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
315	Cytochrome c-mediated apoptotic response	13	0.0059356	-0.4406852	0.0469721
1799	Translesion synthesis by POLI	17	0.0022613	-0.4277365	0.0220502
567	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0000002	-0.4208630	0.0000060
1800	Translesion synthesis by POLK	17	0.0026835	-0.4204902	0.0252698
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

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)

## Dataset saved as " /tmp/Rtmppyg3bi/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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb9e568e22.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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	0.0052507
163	Biosynthesis of E-series 18(S)-resolvins	5	0.0011742	0.8379145	0.0135495
1206	Protein repair	6	0.0009269	0.7806592	0.0114920
309	Cross-presentation of particulate exogenous antigens (phagosomes)	8	0.0002059	0.7576960	0.0036406
1658	Synthesis of 15-eicosatetraenoic acid derivatives	6	0.0027106	0.7068850	0.0240705
1659	Synthesis of 5-eicosatetraenoic acids	7	0.0015472	0.6908802	0.0164719
1657	Synthesis of 12-eicosatetraenoic acid derivatives	6	0.0050614	0.6607666	0.0399723
1105	POLB-Dependent Long Patch Base Excision Repair	8	0.0012739	-0.6577280	0.0142508
1532	Signal attenuation	9	0.0006864	0.6534468	0.0090592
777	Interleukin-21 signaling	9	0.0011824	-0.6242217	0.0135626
1062	OAS antiviral response	8	0.0025806	-0.6152571	0.0232379
805	Keratan sulfate degradation	9	0.0031911	0.5675709	0.0274521
108	Antimicrobial peptides	34	0.0000000	0.5571937	0.0000014
1417	Replacement of protamines by nucleosomes in the male pronucleus	13	0.0005310	0.5549041	0.0074686
280	Cohesin Loading onto Chromatin	10	0.0026724	-0.5483898	0.0238651
1266	RNA Polymerase I Promoter Opening	17	0.0000926	0.5475463	0.0022964
888	Metabolism of Angiotensinogen to Angiotensins	12	0.0010709	0.5453152	0.0127384
942	Mitotic Telophase/Cytokinesis	13	0.0009228	-0.5306344	0.0114920
1430	Response of EIF2AK1 (HRI) to heme deficiency	14	0.0007106	0.5225175	0.0093148
987	NR1H3 & NR1H2 regulate gene expression linked to cholesterol transport and efflux	32	0.0000005	-0.5122321	0.0000299
676	HDR through MMEJ (alt-NHEJ)	12	0.0024693	-0.5046284	0.0224446
1703	TGFBR3 expression	20	0.0001040	-0.5012128	0.0025007
285	Common Pathway of Fibrin Clot Formation	13	0.0017725	0.5006704	0.0181373
1362	Regulation of NPAS4 gene expression	11	0.0051489	-0.4871012	0.0403327
42	Activated PKN1 stimulates transcription of AR (androgen receptor) regulated genes KLK2 and KLK3	20	0.0005133	0.4486247	0.0073387
1674	Synthesis of PIPs at the early endosome membrane	16	0.0021441	-0.4431855	0.0204978
1292	RORA activates gene expression	18	0.0011531	-0.4424563	0.0133852
1818	Transport of Ribonucleoproteins into the Host Nucleus	32	0.0000149	-0.4422366	0.0005512
1666	Synthesis of Leukotrienes (LT) and Eoxins (EX)	16	0.0022643	0.4408289	0.0210428

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)

## Dataset saved as " /tmp/Rtmppyg3bi/dex_crplo_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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb92370496d.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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	-0.7615216	0.0000000
983	NR1H2 & NR1H3 regulate gene expression linked to triglyceride lipolysis in adipose	5	0.0038182	-0.7469746	0.0146861
1508	Scavenging of heme from plasma	71	0.0000000	-0.7389944	0.0000000
307	Creation of C4 and C2 activators	72	0.0000000	-0.7354230	0.0000000
982	NR1H2 & NR1H3 regulate gene expression linked to lipogenesis	8	0.0004599	-0.7151336	0.0024348
879	Maturation of spike protein_9683686	5	0.0057687	-0.7128562	0.0204343
742	Initial triggering of complement	80	0.0000000	-0.6920021	0.0000000
507	FCGR activation	77	0.0000000	-0.6874261	0.0000000
1662	Synthesis of GDP-mannose	6	0.0038070	-0.6821259	0.0146720
180	CD22 mediated BCR regulation	59	0.0000000	-0.6782637	0.0000000
659	Glycosphingolipid transport	7	0.0020856	-0.6716958	0.0089113
557	Formation of annular gap junctions	10	0.0002509	-0.6685636	0.0014387
1010	Negative regulation of TCF-dependent signaling by DVL-interacting proteins	5	0.0099340	-0.6657306	0.0319580
1445	Role of LAT2/NTAL/LAB on calcium mobilization	78	0.0000000	-0.6454780	0.0000000
1647	Sulfide oxidation to sulfate	5	0.0125579	-0.6445461	0.0385951
1837	Type I hemidesmosome assembly	8	0.0016043	-0.6441199	0.0071395
406	Diseases of Base Excision Repair	5	0.0128494	-0.6424423	0.0393066
984	NR1H2 & NR1H3 regulate gene expression to control bile acid homeostasis	7	0.0034395	-0.6384629	0.0134720
985	NR1H2 & NR1H3 regulate gene expression to limit cholesterol uptake	5	0.0137381	-0.6362772	0.0410439
1845	Unwinding of DNA	12	0.0001961	-0.6207720	0.0011699
660	Glyoxylate metabolism and glycine degradation	13	0.0001076	-0.6202519	0.0007150
57	Activation of NIMA Kinases NEK9, NEK6, NEK7	7	0.0045030	-0.6199450	0.0168492
599	G2/M DNA replication checkpoint	5	0.0169757	-0.6164464	0.0489704
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	-0.5991845	0.0000000
1361	Regulation of NFE2L2 gene expression	8	0.0036768	-0.5929924	0.0142845
994	Nef Mediated CD4 Down-regulation	9	0.0021593	-0.5904121	0.0091855
497	Expression and translocation of olfactory receptors	52	0.0000000	0.5867809	0.0000000
508	FCGR3A-mediated IL10 synthesis	100	0.0000000	-0.5835893	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)

## Dataset saved as " /tmp/Rtmppyg3bi/dex_crphi_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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb93b757b61.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
1301	RUNX1 regulates expression of components of tight junctions	5	0.0012360	0.8341366	0.0111590
22	APOBEC3G mediated resistance to HIV-1 infection	5	0.0028411	-0.7706284	0.0224043
180	CD163 mediating an anti-inflammatory response	9	0.0000764	0.7613056	0.0010317
573	Formation of the ureteric bud	5	0.0032989	0.7587524	0.0252913
1303	RUNX1 regulates transcription of genes involved in BCR signaling	6	0.0014667	0.7498750	0.0128216
1141	Phenylalanine metabolism	5	0.0043216	-0.7368737	0.0301423
166	Biosynthesis of Lipoxins (LX)	6	0.0025350	0.7116810	0.0202378
1312	RUNX3 regulates BCL2L11 (BIM) transcription	5	0.0079700	0.6851505	0.0486336
1107	POLB-Dependent Long Patch Base Excision Repair	8	0.0009283	-0.6760152	0.0086378
1127	Peptide chain elongation	88	0.0000000	-0.6601676	0.0000000
495	Eukaryotic Translation Elongation	93	0.0000000	-0.6528697	0.0000000
559	Formation of a pool of free 40S subunits	100	0.0000000	-0.6440267	0.0000000
1454	SARS-CoV-1 modulates host translation machinery	36	0.0000000	-0.6415006	0.0000000
497	Eukaryotic Translation Termination	92	0.0000000	-0.6408672	0.0000000
1867	Viral mRNA Translation	88	0.0000000	-0.6407564	0.0000000
1514	Selenocysteine synthesis	92	0.0000000	-0.6337581	0.0000000
1039	Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	94	0.0000000	-0.5896448	0.0000000
968	NFE2L2 regulates pentose phosphate pathway genes	8	0.0040580	0.5866605	0.0288234
619	GTP hydrolysis and joining of the 60S ribosomal subunit	111	0.0000000	-0.5855131	0.0000000
1814	Translocation of ZAP-70 to Immunological synapse	24	0.0000007	-0.5851460	0.0000163
815	L13a-mediated translational silencing of Ceruloplasmin expression	110	0.0000000	-0.5842927	0.0000000
220	Cap-dependent Translation Initiation	118	0.0000000	-0.5833991	0.0000000
496	Eukaryotic Translation Initiation	118	0.0000000	-0.5833991	0.0000000
182	CD22 mediated BCR regulation	58	0.0000000	0.5790341	0.0000000
1433	Response of EIF2AK4 (GCN2) to amino acid deficiency	100	0.0000000	-0.5728271	0.0000000
572	Formation of the ternary complex, and subsequently, the 43S complex	51	0.0000000	-0.5725261	0.0000000
1510	Scavenging of heme from plasma	70	0.0000000	0.5710638	0.0000000
1460	SARS-CoV-2 modulates host translation machinery	49	0.0000000	-0.5654391	0.0000000
1298	RUNX1 and FOXP3 control the development of regulatory T lymphocytes (Tregs)	9	0.0034659	0.5626396	0.0260547
549	Folding of actin by CCT/TriC	10	0.0021533	-0.5602801	0.0174794

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)

## Dataset saved as " /tmp/Rtmppyg3bi/dex_crplo_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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb967e33e59.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
1303	RUNX1 regulates transcription of genes involved in BCR signaling	6	0.0010000	0.7756407	0.0257593
180	CD163 mediating an anti-inflammatory response	9	0.0000714	0.7644081	0.0051776
580	Fructose metabolism	7	0.0018078	-0.6809359	0.0371566
984	NR1H2 & NR1H3 regulate gene expression linked to lipogenesis	8	0.0013065	-0.6562457	0.0293510
862	MET activates RAP1 and RAC1	10	0.0025036	0.5520033	0.0460669
25	ATF6 (ATF6-alpha) activates chaperone genes	10	0.0026552	0.5487471	0.0479431
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
1149	Phosphorylation of CD3 and TCR zeta chains	27	0.0006383	-0.3796279	0.0203396
1082	PD-1 signaling	28	0.0006014	-0.3745587	0.0196945
924	Mitochondrial RNA degradation	25	0.0012246	0.3735142	0.0288543
693	Hedgehog ligand biogenesis	47	0.0000112	0.3702915	0.0011369
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
989	NR1H3 & NR1H2 regulate gene expression linked to cholesterol transport and efflux	33	0.0002519	-0.3681144	0.0113265
988	NR1H2 and NR1H3-mediated signaling	39	0.0001112	-0.3575802	0.0062242
1448	Role of phospholipids in phagocytosis	88	0.0000000	-0.3538053	0.0000037
700	Hh mutants are degraded by ERAD	42	0.0000823	0.3510801	0.0056794
699	Hh mutants abrogate ligand secretion	43	0.0000724	0.3496973	0.0051776
27	AUF1 (hnRNP D0) binds and destabilizes mRNA	42	0.0000909	0.3489504	0.0057782
1098	PINK1-PRKN Mediated Mitophagy	31	0.0008837	0.3450209	0.0239317
1387	Regulation of activated PAK-2p34 by proteasome mediated degradation	37	0.0004109	0.3355895	0.0154166
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

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)

## Dataset saved as " /tmp/Rtmppyg3bi/dex_crphi_eos_adj_mitchreport.rds ".

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

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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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb94eb7cfa6.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
278	Cohesin Loading onto Chromatin	10	0.0002333	-0.6719578	0.0146291
11	ALK mutants bind TKIs	11	0.0008319	-0.5818661	0.0355146
1670	Synthesis of PIPs at the late endosome membrane	11	0.0012745	-0.5609299	0.0470820
1347	Regulation of IFNG signaling	14	0.0003423	-0.5526895	0.0199260
939	Mitotic Telophase/Cytokinesis	13	0.0010700	-0.5239751	0.0437336
1669	Synthesis of PIPs at the early endosome membrane	16	0.0007126	-0.4886813	0.0333902
759	Interferon alpha/beta signaling	63	0.0000000	-0.4161906	0.0000070
722	Impaired BRCA2 binding to RAD51	35	0.0000866	-0.3833457	0.0063982
1151	Platelet Aggregation (Plug Formation)	28	0.0011224	0.3556756	0.0445232
368	Defective homologous recombination repair (HRR) due to BRCA2 loss of function	41	0.0003846	-0.3204123	0.0211090
404	Diseases of DNA Double-Strand Break Repair	41	0.0003846	-0.3204123	0.0211090
674	HDR through Single Strand Annealing (SSA)	37	0.0008108	-0.3181357	0.0353972
1179	Presynaptic phase of homologous DNA pairing and strand exchange	40	0.0005040	-0.3178263	0.0254781
840	M-decay: degradation of maternal mRNAs by maternally stored factors	41	0.0011729	-0.2928899	0.0445232
697	Homologous DNA Pairing and Strand Exchange	43	0.0011474	-0.2865629	0.0445232
717	ISG15 antiviral mechanism	72	0.0000649	-0.2722094	0.0049842
97	Amplification of signal from unattached kinetochores via a MAD2 inhibitory signal	90	0.0000538	-0.2462516	0.0047015
98	Amplification of signal from the kinetochores	90	0.0000538	-0.2462516	0.0047015
1420	Resolution of Sister Chromatid Cohesion	115	0.0000116	-0.2367004	0.0014831
938	Mitotic Spindle Checkpoint	107	0.0000392	-0.2300543	0.0044334
1521	Separation of Sister Chromatids	167	0.0000085	-0.1996262	0.0012282
231	Cell Cycle Checkpoints	245	0.0000001	-0.1993666	0.0000359
109	Antiviral mechanism by IFN-stimulated genes	140	0.0000467	-0.1992977	0.0046675
446	EML4 and NUDC in mitotic spindle formation	106	0.0005356	-0.1946259	0.0263811
1421	Respiratory Syncytial Virus Infection Pathway	97	0.0009264	-0.1945830	0.0386856
933	Mitotic G1 phase and G1/S transition	138	0.0001315	-0.1885094	0.0093587
594	G2/M Checkpoints	126	0.0002881	-0.1870269	0.0172950
935	Mitotic Metaphase and Anaphase	211	0.0000029	-0.1869018	0.0006127
932	Mitotic Anaphase	210	0.0000033	-0.1862241	0.0006316

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)

## Dataset saved as " /tmp/Rtmppyg3bi/dex_crplo_pod1_adj_mitchreport.rds ".

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

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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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb9727e277d.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
1143	Phosphorylation of Emi1	6	0.0009138	-0.7816005	0.0148757
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
596	G2/M DNA replication checkpoint	5	0.0036433	-0.7507718	0.0426751
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
57	Activation of NIMA Kinases NEK9, NEK6, NEK7	7	0.0023114	-0.6649857	0.0302053
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
874	Maturation of protein 3a_9683673	9	0.0020566	-0.5932132	0.0280191
875	Maturation of protein 3a_9694719	9	0.0020566	-0.5932132	0.0280191
774	Interleukin-21 signaling	9	0.0020792	-0.5925856	0.0281282
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
289	Condensation of Prometaphase Chromosomes	11	0.0026488	-0.5233542	0.0330481
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

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)

## Dataset saved as " /tmp/Rtmppyg3bi/dex_crphi_pod1_adj_mitchreport.rds ".

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

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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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb95373adae.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
Sulfide oxidation to sulfate	-0.7545251	0.4949731	-0.5282637	-0.5489038	-0.6025111	0.2471584	0.5505017	-0.6384078	-0.1764684	-0.5081752	0.7341894	-0.5458601
CD163 mediating an anti-inflammatory response	-0.2419378	0.1677725	0.0896000	0.4071181	0.8194563	0.6062476	0.4283557	-0.2133514	0.8104785	0.7892290	0.2167642	0.3812548
Peptide chain elongation	-0.8125666	0.1859687	-0.6871214	-0.8502657	-0.3450169	-0.3654733	0.3634209	-0.3762251	-0.6537061	0.0018291	0.0459227	0.0140604
Erythrocytes take up oxygen and release carbon dioxide	0.4188823	0.5443656	0.3304026	0.5119959	0.5927977	0.8020588	0.4363173	-0.4133379	0.4066791	0.6093222	-0.0500832	-0.2800272
Biosynthesis of Lipoxins (LX)	-0.3777704	0.4643616	-0.0179460	0.3309553	0.3733473	0.7351057	0.8467929	-0.3734107	0.7175719	0.4230001	0.1980405	-0.2641333
CD22 mediated BCR regulation	-0.5434063	0.3039165	-0.5283960	0.2818184	-0.3707379	0.5136633	0.0573992	-0.6858466	0.5819886	-0.3880618	0.1343947	-0.8074299
Classical antibody-mediated complement activation	-0.6055788	0.2337466	-0.5714839	0.2366283	-0.3002753	0.4439880	0.0598982	-0.7702995	0.5414071	-0.4646803	0.1355419	-0.7482238
Scavenging of heme from plasma	-0.5656917	0.2723522	-0.5353926	0.2745189	-0.2957378	0.4701209	0.1019360	-0.7466122	0.5742865	-0.4416567	0.1230304	-0.7729139
Eukaryotic Translation Elongation	-0.7937409	0.1857523	-0.6691074	-0.8412016	-0.3357367	-0.3537509	0.3476745	-0.3682478	-0.6461619	-0.0055905	0.0392467	-0.0076149
Viral mRNA Translation	-0.8026073	0.1654508	-0.6743151	-0.8344531	-0.3144618	-0.3588418	0.3511721	-0.3616681	-0.6341376	0.0194955	0.0192090	0.0189950
Cohesin Loading onto Chromatin	0.1660832	-0.6739321	0.6198173	0.4808677	0.7625535	-0.4166968	-0.5487204	-0.0164114	0.1694320	0.1614214	-0.6715156	0.0929693
Formation of a pool of free 40S subunits	-0.7830355	0.1421027	-0.6549694	-0.8461827	-0.2844453	-0.4003292	0.3382736	-0.3545033	-0.6368635	0.0320315	0.0164097	0.0377496
SARS-CoV-1 modulates host translation machinery	-0.7824586	0.1985907	-0.6437946	-0.8169784	-0.3477541	-0.3338414	0.3547924	-0.3464813	-0.6330650	0.0455431	0.0399415	-0.0037467
Eukaryotic Translation Termination	-0.7785909	0.1620917	-0.6615798	-0.7963908	-0.3190917	-0.3653567	0.3104310	-0.3567894	-0.6342219	0.0174005	0.0154915	0.0107056
Creation of C4 and C2 activators	-0.5877615	0.2239426	-0.5416768	0.2122167	-0.2970382	0.4103207	0.0596072	-0.7429089	0.5134679	-0.4746466	0.1390666	-0.7140567
Selenocysteine synthesis	-0.7633151	0.1564075	-0.6536748	-0.8104995	-0.3218593	-0.3698686	0.3082732	-0.3558805	-0.6268365	0.0030599	0.0161999	0.0208535
Formation of ATP by chemiosmotic coupling	-0.7950124	0.0566914	-0.8110603	-0.7102037	0.1571911	-0.2972444	0.4226823	-0.5712212	-0.2826813	0.1463354	0.0368932	0.0303017
Phosphorylation of Emi1	-0.3700498	0.1144615	-0.3859190	0.3340150	-0.1590095	0.6344684	-0.3729668	-0.7697454	0.2913853	-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)	-0.7615059	0.1435676	-0.6484042	-0.7688462	-0.3022066	-0.3551181	0.3015010	-0.3495443	-0.5822407	0.0353782	0.0161960	0.0230454
L13a-mediated translational silencing of Ceruloplasmin expression	-0.7470112	0.0927407	-0.6260855	-0.8031015	-0.2257202	-0.4060178	0.3342842	-0.3319919	-0.5761628	0.0547192	-0.0163101	0.0421208
GTP hydrolysis and joining of the 60S ribosomal subunit	-0.7325825	0.0838448	-0.6228103	-0.8006118	-0.2132857	-0.4033814	0.3255494	-0.3164620	-0.5774096	0.0609832	-0.0224444	0.0436922
Cap-dependent Translation Initiation	-0.7175331	0.0864047	-0.6163298	-0.8011495	-0.2145506	-0.3913999	0.3284041	-0.3228252	-0.5752380	0.0523433	-0.0046411	0.0433546
Eukaryotic Translation Initiation	-0.7175331	0.0864047	-0.6163298	-0.8011495	-0.2145506	-0.3913999	0.3284041	-0.3228252	-0.5752380	0.0523433	-0.0046411	0.0433546
FCGR activation	-0.5402853	0.2090433	-0.4379565	0.3015807	-0.2552026	0.3911279	0.0454143	-0.6920501	0.4973975	-0.3641533	0.0269167	-0.7671168
SRP-dependent cotranslational protein targeting to membrane	-0.7526093	0.0568788	-0.6580059	-0.7531116	-0.1997306	-0.3831678	0.3132753	-0.3599647	-0.5357605	0.0936326	-0.0594920	-0.0511363
Fructose catabolism	-0.5632473	0.4345556	-0.2395111	-0.3512151	-0.4317021	-0.2436391	0.6637276	-0.2040329	-0.0863747	-0.6086555	0.6035003	0.3180768
Establishment of Sister Chromatid Cohesion	0.1440075	-0.6911660	0.3358676	0.3256181	0.6824215	-0.4116187	-0.4671216	-0.0020369	0.2428783	0.0274574	-0.7725910	-0.1275132
G2/M DNA replication checkpoint	-0.4509726	-0.2228658	-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	-0.6232550	-0.7559477	-0.2503181	-0.3326906	0.3472951	-0.3133591	-0.5649487	0.0240628	0.0154196	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	-0.5443670	0.2303862	-0.5127740	0.1644885	-0.2806024	0.3753423	0.0621851	-0.6967582	0.4467490	-0.4692648	0.1443222	-0.6351079
Protein repair	-0.6190272	0.0015219	-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	-0.6965396	0.0761539	-0.5713190	-0.7781653	-0.1982513	-0.4180860	0.3084219	-0.2897458	-0.5632201	0.0862769	-0.0426913	0.0370952
Defective binding of VWF variant to GPIb:IX:V	0.2089599	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	0.2089599	0.2105769	-0.2831122	-0.4076378	0.2028915	0.5959481	0.3907643	0.0810292	0.5490179	0.4406430	0.7476388	-0.3901175
NR1H2 & NR1H3 regulate gene expression to limit cholesterol uptake	-0.6387692	0.0837495	-0.2333096	-0.3348742	-0.0784040	0.2864032	-0.2401198	-0.6304561	-0.3628192	-0.2973225	0.6832834	0.3657108
Role of LAT2/NTAL/LAB on calcium mobilization	-0.5183819	0.1807735	-0.4007306	0.2925855	-0.2033006	0.3157066	0.0750080	-0.6485443	0.5086246	-0.3285192	0.0197218	-0.6795768
Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	-0.6781479	0.0270364	-0.5499444	-0.7320316	-0.1406999	-0.4136060	0.3097081	-0.2845458	-0.4856389	0.1017814	-0.0476036	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	-0.6740398	0.0296591	-0.5467360	-0.7274754	-0.1381530	-0.4145510	0.3027344	-0.2867886	-0.4873374	0.1088967	-0.0610542	0.0592556
Ribosomal scanning and start codon recognition	-0.6662239	0.0269578	-0.5559691	-0.7281840	-0.1250875	-0.4083693	0.2987722	-0.2754247	-0.4868951	0.1119613	-0.0600842	0.0702742
Phosphate bond hydrolysis by NUDT proteins	-0.7170036	-0.1222015	-0.5331952	-0.7682215	-0.0642432	-0.4846951	0.2694276	-0.1544896	-0.0441991	0.2996093	-0.1991711	0.0517547
NR1H2 & NR1H3 regulate gene expression linked to lipogenesis	-0.5695515	0.1899853	-0.2834618	0.0876617	-0.0164574	0.3894240	-0.2341015	-0.7106521	-0.3078030	-0.6514697	0.3870576	0.0995291
SARS-CoV-2 modulates host translation machinery	-0.6054610	0.1771181	-0.5917161	-0.6844793	-0.2600949	-0.2685410	0.2852562	-0.2885747	-0.5566421	0.0148721	0.0417802	0.0057919
Selenoamino acid metabolism	-0.6608394	0.0921778	-0.5610890	-0.6952100	-0.2299740	-0.3152133	0.2569549	-0.3057754	-0.5207653	0.0335160	-0.0073436	0.0511655
Type I hemidesmosome assembly	-0.2403800	0.1955028	-0.0031036	0.4687619	0.1227645	0.5536411	-0.0888152	-0.6382468	-0.1166405	-0.4763009	0.0843203	-0.7222460
Mitochondrial translation elongation	-0.5637899	0.0983224	-0.6863517	-0.6750040	-0.1960048	-0.3562018	0.1953077	-0.3690935	-0.4598319	0.0665351	-0.0071351	-0.0872250
Synthesis of PIPs at the late endosome membrane	0.3690898	-0.6200596	0.3203766	0.2173022	0.3845548	-0.5007763	-0.3509953	0.3139761	0.4140838	0.0346623	-0.5601714	0.1896675
Mitochondrial translation initiation	-0.5407167	0.0718492	-0.6742442	-0.6913507	-0.2064517	-0.3705249	0.1743100	-0.3467482	-0.4661669	0.0721983	-0.0241885	-0.1093242

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

## Dataset saved as " /tmp/Rtmppyg3bi/multireactomestratified_all_mitchreport.rds ".

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

## 1/36                             
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## 8/36 [scatterplot]

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## 10/36 [contourplot]

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## 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]

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## 25/36 [results_table]             
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## 29/36 [detailed_geneset_reports1d]
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## 31/36 [detailed_geneset_reports2d]

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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/Rtmppyg3bi/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/Rtmppyg3bi/rmarkdown-strb91f85a897.html

## 
## Output created: /tmp/Rtmppyg3bi/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<0.05),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
Biosynthesis of Lipoxins (LX)	-0.3868307	0.4632882	0.8454232	-0.3818301
NR1H2 & NR1H3 regulate gene expression linked to triglyceride lipolysis in adipose	-0.6481500	0.3622868	-0.2136474	-0.7469746
Formation of ATP by chemiosmotic coupling	-0.7990801	0.0544165	0.4209428	-0.5772723
Protein repair	-0.6253659	-0.0012349	0.7806592	-0.3025521
Biosynthesis of E-series 18(S)-resolvins	-0.3304002	0.3749646	0.8379145	-0.3231008
Formation of annular gap junctions	-0.7471180	0.1116743	0.1898628	-0.6685636
Glycosphingolipid transport	-0.7715645	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	0.1840352	0.3611089	-0.3851675
Classical antibody-mediated complement activation	-0.5799410	0.2412294	0.0550170	-0.7615216
Viral mRNA Translation	-0.8061739	0.1635183	0.3489081	-0.3707462
NR1H2 & NR1H3 regulate gene expression linked to lipogenesis	-0.5769143	0.1882948	-0.2344365	-0.7151336
Eukaryotic Translation Elongation	-0.7971237	0.1838103	0.3454124	-0.3770738
Scavenging of heme from plasma	-0.5418281	0.2787277	0.0956673	-0.7389944
Biosynthesis of EPA-derived SPMs	-0.1458105	0.3766770	0.8614770	-0.1085651
Creation of C4 and C2 activators	-0.5634755	0.2314063	0.0548751	-0.7354230
PTK6 Regulates RTKs and Their Effectors AKT1 and DOK1	-0.6469309	0.3037932	0.2865428	-0.5637589
SARS-CoV-1 modulates host translation machinery	-0.7859556	0.1967523	0.3526406	-0.3557321
Phosphorylation of Emi1	-0.3787809	0.1116295	-0.3726979	-0.7738901
Formation of a pool of free 40S subunits	-0.7868622	0.1401693	0.3360021	-0.3634243
Fructose metabolism	-0.6674355	0.2927255	0.4698153	-0.3434831
Formyl peptide receptors bind formyl peptides and many other ligands	-0.6187166	-0.2694768	0.5605883	-0.3120406
Eukaryotic Translation Termination	-0.7823329	0.1601679	0.3082801	-0.3658242
Diseases of Mismatch Repair (MMR)	0.2591996	-0.6835308	-0.5528013	0.0672765
Selenocysteine synthesis	-0.7670404	0.1543684	0.3061428	-0.3647636
Erythrocytes take up oxygen and release carbon dioxide	0.4114257	0.5430636	0.4343869	-0.4185480
CD22 mediated BCR regulation	-0.5144745	0.3109324	0.0517504	-0.6782637
Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	-0.7653675	0.1415911	0.2993970	-0.3584511
Prevention of phagosomal-lysosomal fusion	-0.6614875	0.1074415	0.2848147	-0.5366584
Initial triggering of complement	-0.5245250	0.2368231	0.0577650	-0.6920021
Nef Mediated CD4 Down-regulation	-0.6542397	0.1736476	0.0548465	-0.5904121
SRP-dependent cotranslational protein targeting to membrane	-0.7565191	0.0546691	0.3111155	-0.3687116
Glyoxylate metabolism and glycine degradation	-0.5337315	0.2109059	0.3005585	-0.6202519
L13a-mediated translational silencing of Ceruloplasmin expression	-0.7511557	0.0906364	0.3320244	-0.3408256
VLDLR internalisation and degradation	-0.6602212	0.1634927	0.1365576	-0.5604545
FCGR activation	-0.5198756	0.2162788	0.0412387	-0.6874261
Cohesin Loading onto Chromatin	0.1552242	-0.6764959	-0.5483898	-0.0270357
Response of EIF2AK4 (GCN2) to amino acid deficiency	-0.7211906	0.1495303	0.3450670	-0.3223494
GTP hydrolysis and joining of the 60S ribosomal subunit	-0.7368616	0.0817371	0.3233155	-0.3252782
NR1H2 & NR1H3 regulate gene expression to control bile acid homeostasis	-0.3967107	0.0672304	-0.4348443	-0.6384629
Pentose phosphate pathway	-0.6339705	-0.0634931	0.3574599	-0.4669196
SUMO is conjugated to E1 (UBA2:SAE1)	-0.6688772	-0.4728013	-0.0018934	-0.2823233
Cap-dependent Translation Initiation	-0.7220008	0.0842917	0.3262232	-0.3316619
Eukaryotic Translation Initiation	-0.7220008	0.0842917	0.3262232	-0.3316619
Synthesis of PIPs at the late endosome membrane	0.3589327	-0.6226559	-0.3514550	0.3058653
Synthesis of 5-eicosatetraenoic acids	-0.2730314	0.3411831	0.6908802	-0.2537425
Retrograde neurotrophin signalling	-0.5940693	0.0922088	0.1446610	-0.5821743
Regulation of NFE2L2 gene expression	0.0365131	0.4139031	-0.4436465	-0.5929924
Establishment of Sister Chromatid Cohesion	0.1342447	-0.6938228	-0.4668973	-0.0118403
Role of LAT2/NTAL/LAB on calcium mobilization	-0.4986892	0.1885307	0.0699845	-0.6454780

#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<0.05),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	-0.6817694	-0.8467468	-0.6601676	-0.0088250
Formation of xylulose-5-phosphate	-0.5771756	-0.6573065	-0.5937074	-0.6981359
Eukaryotic Translation Elongation	-0.6645020	-0.8382493	-0.6528697	-0.0159734
Formation of a pool of free 40S subunits	-0.6511768	-0.8436038	-0.6440267	0.0213389
Viral mRNA Translation	-0.6691139	-0.8310977	-0.6407564	0.0086248
SARS-CoV-1 modulates host translation machinery	-0.6478547	-0.8200737	-0.6415006	0.0368423
Selenocysteine synthesis	-0.6491205	-0.8080453	-0.6337581	-0.0075308
Eukaryotic Translation Termination	-0.6569629	-0.7940136	-0.6408672	0.0066784
Phenylalanine metabolism	-0.4336092	-0.5974175	-0.7368737	-0.5580431
L13a-mediated translational silencing of Ceruloplasmin expression	-0.6233874	-0.8017335	-0.5842927	0.0441367
GTP hydrolysis and joining of the 60S ribosomal subunit	-0.6202008	-0.7993446	-0.5855131	0.0503398
Cap-dependent Translation Initiation	-0.6142424	-0.8001803	-0.5833991	0.0418860
Eukaryotic Translation Initiation	-0.6142424	-0.8001803	-0.5833991	0.0418860
Nonsense Mediated Decay (NMD) independent of the Exon Junction Complex (EJC)	-0.6441588	-0.7669569	-0.5896448	0.0245402
MET activates PI3K/AKT signaling	0.7768482	0.3518596	0.5666454	0.5409112
SRP-dependent cotranslational protein targeting to membrane	-0.6547847	-0.7527980	-0.5445297	0.0826106
Response of EIF2AK4 (GCN2) to amino acid deficiency	-0.6197982	-0.7547504	-0.5728271	0.0136207
Formation of ATP by chemiosmotic coupling	-0.8137677	-0.7152418	-0.2941399	0.1376132
Formation of the ternary complex, and subsequently, the 43S complex	-0.5757262	-0.7819123	-0.5725261	0.0777042
CD163 mediating an anti-inflammatory response	0.0480623	0.2985903	0.7613056	0.7644081
Mitochondrial translation initiation	-0.6774720	-0.6964576	-0.4755113	0.0641177
Mitochondrial translation elongation	-0.6894701	-0.6802258	-0.4692247	0.0584985
SARS-CoV-2 modulates host translation machinery	-0.5956878	-0.6889052	-0.5654391	0.0063038
Mitochondrial translation termination	-0.6604115	-0.6820556	-0.4651817	0.0643845
Ribosomal scanning and start codon recognition	-0.5604419	-0.7322003	-0.4964709	0.1035426
Activation of the mRNA upon binding of the cap-binding complex and eIFs, and subsequent binding to 43S	-0.5544242	-0.7359996	-0.4952922	0.0933841
Translation initiation complex formation	-0.5512181	-0.7315119	-0.4969189	0.1005141
Mitochondrial translation	-0.6410100	-0.6716403	-0.4664192	0.0619103
APOBEC3G mediated resistance to HIV-1 infection	-0.4541966	-0.5093935	-0.7706284	-0.1338001
Selenoamino acid metabolism	-0.5591625	-0.6956466	-0.5290417	0.0233937
YAP1- and WWTR1 (TAZ)-stimulated gene expression	0.2499740	0.6403108	0.5628021	0.4595827
Folding of actin by CCT/TriC	-0.5636091	-0.5241712	-0.5602801	0.3065351
Nonsense Mediated Decay (NMD) enhanced by the Exon Junction Complex (EJC)	-0.5284602	-0.6619947	-0.5282157	0.0414151
Nonsense-Mediated Decay (NMD)	-0.5284602	-0.6619947	-0.5282157	0.0414151
Regulation of expression of SLITs and ROBOs	-0.5355496	-0.6597398	-0.5008585	0.1047324
Arachidonate production from DAG	-0.8172956	-0.4496135	0.1968173	-0.2642175
Phosphate bond hydrolysis by NUDT proteins	-0.5383516	-0.7730733	-0.0518890	0.2935613
Translation	-0.6010697	-0.6187902	-0.4696740	0.0594551
LTC4-CYSLTR mediated IL4 production	0.2796581	-0.5652996	-0.3885787	-0.6465763
Vpu mediated degradation of CD4	-0.4668044	-0.6472094	-0.4826187	0.2852529
RUNX1 and FOXP3 control the development of regulatory T lymphocytes (Tregs)	0.0383103	0.6761356	0.5626396	0.3958365
Vif-mediated degradation of APOBEC3G	-0.5064436	-0.6276950	-0.4230160	0.3191525
Complex III assembly	-0.6616507	-0.6002002	-0.3216513	-0.0227481
Classical antibody-mediated complement activation	-0.5773337	0.2385205	0.5380004	-0.4676725
Scavenging of heme from plasma	-0.5418487	0.2753666	0.5710638	-0.4449581
Regulation of activated PAK-2p34 by proteasome mediated degradation	-0.4718913	-0.6079543	-0.4271481	0.3355895
Erythrocytes take up oxygen and release carbon dioxide	0.3270930	0.5045991	0.3980279	0.6015564
Cristae formation	-0.6654665	-0.5625360	-0.3297438	0.1157547
Ubiquitin Mediated Degradation of Phosphorylated Cdc25A	-0.5150297	-0.6186750	-0.4133016	0.2479403

#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<0.05),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
MET activates PI3K/AKT signaling	0.8254330	-0.4128765	-0.7084149	0.2996047
Sulfide oxidation to sulfate	-0.6046498	0.2428840	0.7347139	-0.5468750
Establishment of Sister Chromatid Cohesion	0.6802647	-0.4141024	-0.7731595	-0.1288870
CD163 mediating an anti-inflammatory response	0.8177689	0.6035067	0.2168863	0.3802659
Cohesin Loading onto Chromatin	0.7607588	-0.4192252	-0.6719578	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	-0.3651902	0.5163091	0.1233733	-0.8108614
Erythrocytes take up oxygen and release carbon dioxide	0.5902422	0.8004330	-0.0507793	-0.2809941
Wax and plasmalogen biosynthesis	0.5824548	-0.6010730	-0.5730422	0.1153238
Phosphorylation of Emi1	-0.1619366	0.6310224	-0.0675076	-0.7816005
Scavenging of heme from plasma	-0.2925311	0.4724193	0.1140281	-0.7763233
NFE2L2 regulates pentose phosphate pathway genes	0.7738762	0.4843257	0.2343375	0.1040598
Activation of caspases through apoptosome-mediated cleavage	0.3170957	-0.5045104	-0.6727852	-0.2985206
Classical antibody-mediated complement activation	-0.2970563	0.4468521	0.1261904	-0.7520661
Type I hemidesmosome assembly	0.1201106	0.5509885	0.0846317	-0.7228054
ARMS-mediated activation	0.5235092	-0.3156681	-0.6580066	-0.1803549
FCGR activation	-0.2529979	0.3941056	0.0198117	-0.7704262
Fructose metabolism	-0.4634688	-0.3649225	0.6109251	0.2831323
Creation of C4 and C2 activators	-0.2940605	0.4135334	0.1299429	-0.7183099
Biosynthesis of Lipoxins (LX)	0.3713465	0.7323387	0.1977691	-0.2654649
Neurotransmitter clearance	0.2082490	0.0614518	0.6183147	0.5651621
Synthesis of PIPs at the late endosome membrane	0.3813714	-0.5026748	-0.5609299	0.1882719
Response to metal ions	0.5292826	0.5816821	-0.1616228	-0.2811377
Fructose catabolism	-0.4336032	-0.2466867	0.6036145	0.3166039
SMAC (DIABLO) binds to IAPs	0.2033458	-0.4876750	-0.5429593	-0.3550114
SMAC(DIABLO)-mediated dissociation of IAP:caspase complexes	0.2033458	-0.4876750	-0.5429593	-0.3550114
SMAC, XIAP-regulated apoptotic response	0.2033458	-0.4876750	-0.5429593	-0.3550114
SUMO is proteolytically processed	0.1992281	-0.5487990	-0.5182692	-0.2758664
Scavenging by Class A Receptors	0.6578261	0.1282587	-0.2197147	0.4144330
Common Pathway of Fibrin Clot Formation	0.2776474	0.4569535	0.1834275	-0.5754020
Initial triggering of complement	-0.2784248	0.3783444	0.1360864	-0.6400733
Lysosphingolipid and LPA receptors	-0.4813363	0.3257954	0.3417329	-0.4321884
Unwinding of DNA	-0.3673164	0.2302230	-0.0271566	-0.6684557
Mitotic Telophase/Cytokinesis	0.5578154	-0.1762639	-0.5239751	-0.1138998
Regulation of IFNG signaling	0.5575525	-0.0247187	-0.5526895	0.0013654
Role of LAT2/NTAL/LAB on calcium mobilization	-0.2018372	0.3194943	0.0128435	-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	0.1109373
OAS antiviral response	-0.1582843	-0.3463168	-0.5184514	-0.4216286
Protein repair	0.4695408	0.1666431	0.0329458	-0.5619774
Microtubule-dependent trafficking of connexons from Golgi to the plasma membrane	0.2936381	0.5563690	0.2653438	-0.3115437
Transport of connexons to the plasma membrane	0.2936381	0.5563690	0.2653438	-0.3115437
Butyrophilin (BTN) family interactions	-0.4953255	-0.2848091	0.4091889	0.2622605

#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] RhpcBLASctl_0.23-42         gtools_3.9.5               
##  [3] xlsx_0.6.5                  DT_0.34.0                  
##  [5] ggplot2_4.0.3               kableExtra_1.4.0           
##  [7] beeswarm_0.4.0              eulerr_7.1.0               
##  [9] MASS_7.3-65                 mitch_1.22.1               
## [11] DESeq2_1.50.2               SummarizedExperiment_1.40.0
## [13] Biobase_2.70.0              MatrixGenerics_1.22.0      
## [15] matrixStats_1.5.0           GenomicRanges_1.62.1       
## [17] Seqinfo_1.0.0               IRanges_2.44.0             
## [19] S4Vectors_0.48.1            BiocGenerics_0.56.0        
## [21] generics_0.1.4              dplyr_1.2.1                
## [23] WGCNA_1.74                  fastcluster_1.3.0          
## [25] dynamicTreeCut_1.63-1       reshape2_1.4.5             
## [27] 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] crosstalk_1.2.2       Hmisc_5.2-5           labeling_0.4.3       
##  [37] polyclip_1.10-7       abind_1.4-8           compiler_4.5.2       
##  [40] withr_3.0.2           doParallel_1.0.17     htmlTable_2.5.0      
##  [43] S7_0.2.2              backports_1.5.1       BiocParallel_1.44.0  
##  [46] ggstats_0.13.0        DelayedArray_0.36.1   caTools_1.18.3       
##  [49] tools_4.5.2           foreign_0.8-90        otel_0.2.0           
##  [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_1.18.2.1   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