Introduction

Here I will use fry to perform GMEA analysis.

suppressPackageStartupMessages({
  library("plyr")
  library("R.utils")
  library("missMethyl")
  library("limma")
  library("DMRcate")
  library("DMRcatedata")
  library("topconfects")
  library("minfi")
  library("IlluminaHumanMethylation450kmanifest")
  library("RColorBrewer")
  library("IlluminaHumanMethylationEPICanno.ilm10b4.hg19")
  library("GEOquery")
  library("eulerr")
  library("plyr")
  library("gplots")
  library("reshape2")
  library("forestplot")
  library("beeswarm")
  library("RCircos")
  library("qqman")
  library("ENmix")

  library("tictoc")
  library("kableExtra")
  library("mitch")
  library("fgsea")

})

source("../meth_functions.R")

Load data

load("GSE158422.Rdata")

anno <- getAnnotation(IlluminaHumanMethylationEPICanno.ilm10b4.hg19)
myann <- data.frame(anno[,c("UCSC_RefGene_Name","Regulatory_Feature_Group","Islands_Name","Relation_to_Island")])
promoters <- grep("Prom",myann$Regulatory_Feature_Group)
promoters <- myann[promoters,]

Curate probe-sets.

Firstly for whole gene.

gp <- myann[,"UCSC_RefGene_Name",drop=FALSE]
gp2 <- strsplit(gp$UCSC_RefGene_Name,";")
names(gp2) <- rownames(gp)
sets <- split(rep(names(gp2), lengths(gp2)), unlist(gp2))

summary(unlist(lapply(sets,length)))
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    1.00    9.00   24.00   49.68   55.00 6778.00

Now for promoters only.

gp <- promoters[,"UCSC_RefGene_Name",drop=FALSE]
gp2 <- strsplit(gp$UCSC_RefGene_Name,";")
names(gp2) <- rownames(gp)
psets <- split(rep(names(gp2), lengths(gp2)), unlist(gp2))

summary(unlist(lapply(psets,length)))
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    1.00    8.00   15.00   21.27   26.00  536.00

Design matrix

samplesheet<-targets
groups <- factor(samplesheet$case,levels=c("tumor: normal","tumor: tumor"))
sex <- factor(samplesheet$sex,levels=c("0","1"))
design <- model.matrix(~ sex + groups)
mxs <- Mval

set up mroast

Roast is a self contained test involving sample permulations.

This is beneficial for two reasons.

  1. Sample permutations will prevent against false positives caused by strong probe-probe correlation structures.

  2. Competitive tests are not suited to experiments where there are unequal up and down regulaiton, which is common for epigenetics studies.

Parallel analysis of GMEA with whole gene and promoters only.

mroast with 1000 whole gene probe sets, 2000 rotations: 42 s

mroast with 1000 gene promoter probe sets, 2000 rotations: 41 s

tic()
mro_res1 <- mroast(y=mxs, index = head(sets,1000), design = design, contrast = ncol(design), nrot = 2000 )
toc()
## 78.889 sec elapsed
head(mro_res1,20) %>%
  kbl(caption="mroast test with 1000 whole gene probe sets") %>%
  kable_styling(full_width=FALSE)
mroast test with 1000 whole gene probe sets
NGenes PropDown PropUp Direction PValue FDR PValue.Mixed FDR.Mixed
ACTA1 26 0 1 Up 0.0004998 0.0007825 0.0004998 0.0004998
ACY3 20 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
AGXT 18 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ABP1 15 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ADAM29 14 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ACTBL2 13 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ADAM6 12 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
APOA4 12 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ANKS4B 10 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ABCC6P1 9 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ADAM3A 9 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ALAS2 9 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
AAA1 8 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ACCSL 8 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ADAM21 8 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
AKAP4 8 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ALKBH3-AS1 8 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ANKRD7 8 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ADGRE1 7 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998
ADGRF4 7 1 0 Down 0.0004998 0.0007825 0.0004998 0.0004998 
tic()
mro_res2 <- mroast(y=mxs, index = head(psets,1000), design = design, contrast = ncol(design), nrot = 2000 )
toc()
## 65.505 sec elapsed
head(mro_res2,20) %>%
  kbl(caption="mroast test with 1000 promoter only probe sets") %>%
  kable_styling(full_width=FALSE)
mroast test with 1000 promoter only probe sets
NGenes PropDown PropUp Direction PValue FDR PValue.Mixed FDR.Mixed
ABLIM1 12 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
AMIGO3 11 0 1 Up 0.0004998 0.0025497 0.0004998 0.0012814
BAHCC1 8 0 1 Up 0.0004998 0.0025497 0.0004998 0.0012814
ACSM3 7 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
AIM2 7 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
ARHGAP15 7 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
APBA2 6 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
ADORA3 5 0 1 Up 0.0004998 0.0025497 0.0004998 0.0012814
ARL11 5 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
ABI3 4 0 1 Up 0.0004998 0.0025497 0.0004998 0.0012814
AMZ1 4 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
AOAH 4 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
ALOX5AP 3 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
ARHGEF39 3 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
BFSP1 3 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
ANKRD13B 2 0 1 Up 0.0004998 0.0025497 0.0004998 0.0012814
BRK1 2 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
ACOXL 1 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
ACSM1 1 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814
ADORA2A 1 1 0 Down 0.0004998 0.0025497 0.0004998 0.0012814

Set up fry test

Fry is good because the p-values are analytically determined, and will have high precision.

Small test whole gene: 28 secs. Small test gene promoter: 27 secs.

tic()
fry_res1 <- fry(y=mxs, index = head(sets,1000), design = design, contrast = ncol(design) )
toc()
## 49.518 sec elapsed
head(fry_res1,20) %>%
  kbl(caption="fry test with 1000 whole gene probe sets") %>%
  kable_styling(full_width=FALSE)
fry test with 1000 whole gene probe sets
NGenes Direction PValue FDR PValue.Mixed FDR.Mixed
ADCY10P1 2 Down 0 0e+00 0.5397457 0.6574248
ACTG1P17 3 Down 0 0e+00 0.3898835 0.5050304
ABP1 15 Down 0 0e+00 0.0017633 0.0040258
ALOX5AP 31 Down 0 0e+00 0.0000000 0.0000000
AP1S1 19 Down 0 0e+00 0.0000025 0.0000091
ACY3 20 Down 0 0e+00 0.0005862 0.0014474
ADPRM 4 Down 0 0e+00 0.2587117 0.3515105
ADAM28 20 Down 0 0e+00 0.0000260 0.0000781
ADGRE1 7 Down 0 0e+00 0.0979095 0.1510949
AGER 20 Up 0 0e+00 0.0000119 0.0000384
ACSM2B 5 Down 0 0e+00 0.2040112 0.2873397
AOC1 6 Down 0 1e-07 0.1506730 0.2202822
ADM5 5 Up 0 1e-07 0.1925362 0.2731011
AMY1A 3 Down 0 1e-07 0.4005399 0.5148327
AMY1B 3 Down 0 1e-07 0.4005399 0.5148327
AMY1C 3 Down 0 1e-07 0.4005399 0.5148327
ACTR3BP2 1 Down 0 1e-07 0.0000000 0.0000000
ABCC12 28 Down 0 1e-07 0.0000194 0.0000601
ABHD5 29 Down 0 1e-07 0.0000000 0.0000001
AARS2 26 Down 0 1e-07 0.0000002 0.0000009 
tic()
fry_res2 <- fry(y=mxs, index = head(psets,1000), design = design, contrast = ncol(design) )
toc()
## 43.647 sec elapsed
head(fry_res2,20) %>%
  kbl(caption="fry test with 1000 gene promoter probe sets") %>%
  kable_styling(full_width=FALSE)
fry test with 1000 gene promoter probe sets
NGenes Direction PValue FDR PValue.Mixed FDR.Mixed
ABLIM1 12 Down 0 0.0e+00 0.0002405 0.0096218
ATIC 15 Down 0 0.0e+00 0.0000203 0.0014524
ACSM3 7 Down 0 0.0e+00 0.0459740 0.5675798
AARS2 11 Down 0 0.0e+00 0.0013047 0.0420871
ANK3 1 Down 0 0.0e+00 0.0000000 0.0000000
BLACAT1 1 Down 0 0.0e+00 0.0000000 0.0000000
ARMC5 27 Down 0 0.0e+00 0.0000000 0.0000024
AIM2 7 Down 0 0.0e+00 0.0690251 0.7502727
ARL11 5 Down 0 0.0e+00 0.1483576 1.0000000
ARAP2 4 Down 0 0.0e+00 0.5777628 1.0000000
AOAH 4 Down 0 0.0e+00 0.2495297 1.0000000
ALOX5AP 3 Down 0 1.0e-07 0.3768062 1.0000000
BCL2 18 Down 0 1.0e-07 0.0000544 0.0032002
BNIPL 1 Down 0 1.0e-07 0.0000000 0.0000004
ABCA2 10 Down 0 2.0e-07 0.0126815 0.2181577
BCL11A 11 Down 0 2.0e-07 0.0034999 0.0856324
ANKRD31 11 Down 0 4.0e-07 0.1427738 1.0000000
AURKB 10 Down 0 5.0e-07 0.0202633 0.3142293
ARHGEF2 17 Up 0 1.1e-06 0.0001376 0.0062554
ALDOA 14 Down 0 1.2e-06 0.0094893 0.1757287

Now we can run the test with all probe sets.

Whole gene: 639 sec (10.5 mins)

Promoter: 261 sec (4.35 mins)

tic()
fry_res1 <- fry(y=mxs, index = sets, design = design, contrast = ncol(design) )
toc()
## 1211.034 sec elapsed
head(fry_res1,20) %>%
  kbl(caption="fry test with all whole gene probe sets") %>%
  kable_styling(full_width=FALSE)
fry test with all whole gene probe sets
NGenes Direction PValue FDR PValue.Mixed FDR.Mixed
DLG3-AS1 4 Down 0 0 0.1133955 0.2102130
MAB21L2 19 Up 0 0 0.0000014 0.0000072
FAM53B-AS1 9 Up 0 0 0.0034667 0.0099574
LOC100506472 4 Up 0 0 0.1128079 0.2094074
REXO1L1 3 Down 0 0 0.2183037 0.3588647
TSTD1 16 Down 0 0 0.0000269 0.0001165
PFN3 10 Up 0 0 0.0041681 0.0117558
LINC00312 1 Up 0 0 0.0000000 0.0000000
LOC158376 5 Up 0 0 0.0766042 0.1514921
SPATA12 9 Down 0 0 0.0072676 0.0194096
HOXA-AS2 7 Up 0 0 0.0283074 0.0645610
MAP1LC3B2 18 Down 0 0 0.0000252 0.0001099
MIR26A1 7 Up 0 0 0.0223238 0.0523765
MIR550-2 3 Down 0 0 0.3408467 0.5084735
C10orf91 10 Down 0 0 0.0034029 0.0097936
LOC101929551 6 Down 0 0 0.0536706 0.1121701
OR6Q1 1 Down 0 0 0.0000000 0.0000000
P2RY10 7 Down 0 0 0.0305306 0.0689344
REXO1L2P 7 Down 0 0 0.0144280 0.0356549
MIR4752 4 Down 0 0 0.1683733 0.2904473 
tic()
fry_res2 <- fry(y=mxs, index = psets, design = design, contrast = ncol(design) )
toc()
## 498.446 sec elapsed
head(fry_res2,20) %>%
  kbl(caption="fry test with all gene promoter probe sets") %>%
  kable_styling(full_width=FALSE)
fry test with all gene promoter probe sets
NGenes Direction PValue FDR PValue.Mixed FDR.Mixed
TSTD1 11 Down 0 0 0.0012755 0.0473509
ABLIM1 12 Down 0 0 0.0002405 0.0118440
LOXL1-AS1 3 Down 0 0 0.2778737 1.0000000
PTPN6 17 Down 0 0 0.0000134 0.0011763
SYTL1 12 Down 0 0 0.0012784 0.0473509
DTNA 1 Down 0 0 0.0000000 0.0000000
GNA15 6 Down 0 0 0.0430440 0.6232083
MIF-AS1 1 Down 0 0 0.0000000 0.0000000
MIR19B1 1 Down 0 0 0.0000000 0.0000000
MIR20A 1 Down 0 0 0.0000000 0.0000000
EFNA4 15 Down 0 0 0.0000243 0.0018680
RNF216 18 Down 0 0 0.0000017 0.0002058
ATIC 15 Down 0 0 0.0000203 0.0016393
LOXL1 8 Down 0 0 0.0124503 0.2700764
MIR4757 1 Down 0 0 0.0000000 0.0000000
MYB 9 Down 0 0 0.0079494 0.1900515
NIPSNAP1 8 Down 0 0 0.0171737 0.3366365
SLC25A24 5 Down 0 0 0.0709197 0.8682678
UBXN11 21 Down 0 0 0.0000002 0.0000357
GCSAM 1 Down 0 0 0.0000000 0.0000000

Pathway analysis

Simple GSEA using FGSEA (gene permutation) and mitch (rank-ANOVA).

#download.file("https://reactome.org/download/current/ReactomePathways.gmt.zip", destfile="ReactomePathways.gmt.zip")
#unzip("ReactomePathways.gmt.zip")
genesets <- gmt_import("ReactomePathways.gmt")

stat1 <- sign(as.numeric(factor(fry_res1$Direction))-1.5)  * -log10(fry_res1$PValue)
stat1[is.na(stat1)] <- 0
names(stat1) <- rownames(fry_res1)
fres1 <- fgseaMultilevel(pathways=genesets,stats=stat1)
## Warning in preparePathwaysAndStats(pathways, stats, minSize, maxSize, gseaParam, : There are ties in the preranked stats (0.78% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.
## Warning in fgseaMultilevel(pathways = genesets, stats = stat1): There were
## 12 pathways for which P-values were not calculated properly due to unbalanced
## (positive and negative) gene-level statistic values. For such pathways pval,
## padj, NES, log2err are set to NA. You can try to increase the value of the
## argument nPermSimple (for example set it nPermSimple = 10000)
## Warning in fgseaMultilevel(pathways = genesets, stats = stat1): For some
## pathways, in reality P-values are less than 1e-50. You can set the `eps`
## argument to zero for better estimation.
fres1 <- fres1[order(fres1$pval),]

head(fres1,20) %>%
  kbl(caption="WG fry + fgsea Reactome results") %>%
  kable_styling(full_width=FALSE)
WG fry + fgsea Reactome results
pathway pval padj log2err ES NES size leadingEdge
Expression and translocation of olfactory receptors 0.0000000 0.0000000 NA -0.6991619 -2.127143 373 OR6Q1 , OR9I1 , OR1S2 , OR51I1 , OR6P1 , OR10W1 , OR2T29 , OR5H1 , OR4C3 , OR3A2 , OR8B8 , OR5H6 , OR1S1 , OR2B11 , OR14J1 , OR10K2 , OR5B2 , OR10J3 , OR2M7 , OR2M4 , OR1L1 , OR52D1 , OR5AC2 , OR4D1 , OR10C1 , OR56A1 , OR10G8 , OR8H2 , OR10Z1 , OR52A5 , OR2G2 , OR4D10 , OR10G9 , OR5W2 , OR13G1 , OR4D9 , OR8B12 , OR8K3 , OR2T12 , OR5H14 , OR1B1 , OR2T5 , OR5B3 , OR52E2 , OR9Q2 , OR10J1 , OR2M5 , OR5J2 , OR2AP1 , OR4D11 , OR6Y1 , OR6K2 , OR52E6 , OR5B17 , OR5B21 , OR4C16 , OR5B12 , OR9Q1 , OR10J5 , OR6N1 , OR1N1 , OR4E2 , OR10Q1 , OR2L5 , OR51B6 , OR5AP2 , OR8J3 , OR5T2 , OR5AS1 , OR52A1 , OR8U1 , OR51F1 , OR10G4 , OR12D2 , OR5A1 , OR14I1 , OR6N2 , OR8K5 , OR6B1 , OR56B1 , OR4F15 , OR6F1 , OR11A1 , OR5F1 , OR4A15 , OR10A5 , OR51E1 , OR7G3 , OR8B4 , OR5M8 , OR4A16 , OR51I2 , OR8U8 , OR6C75 , OR2W5 , OR5I1 , OR9G9 , OR9G1 , OR51B5 , OR4D5 , OR4D6 , OR10AG1, OR2F1 , OR2AG2 , OR5T3 , OR5AU1 , OR51T1 , OR51B2 , OR11L1 , OR51F2 , OR5V1 , OR2A25 , OR2G3 , OR52N4 , OR2G6 , OR8J1 , OR8D1 , OR2J2 , OR2L8 , OR2B3 , OR1K1 , OR8A1 , OR5M9 , OR2A12 , OR52J3 , OR52E4 , OR52H1 , OR4C46 , OR4K5 , OR52R1 , OR9G4 , OR1J2 , OR4C15 , OR2T6 , OR2T33 , OR56A5 , OR52L1 , OR5M3 , OR6K6 , OR2M3 , OR8G5 , OR10T2 , OR51A7 , OR10K1 , OR1C1 , OR2Z1 , OR51B4 , OR8H3 , OR8G1 , OR10X1 , OR2W1 , OR2M2 , OR5M1 , OR51Q1 , OR2AE1 , OR2A2 , OR14A16, OR2T34 , OR5AR1 , OR3A3 , OR8I2 , OR51A2 , OR5L1 , OR9A2 , OR51D1 , OR14C36, OR4K13 , OR52B2 , OR1M1 , OR52W1 , OR2A4 , OR52K2 , OR4A47 , OR52N1 , OR10A4 , OR5D13 , OR5D18 , OR4S1 , OR8K1 , OR2Y1 , OR8B2 , OR2T3 , OR5AK2 , OR52E8 , OR2W3 , OR51G1 , OR5L2 , OR5A2 , OR2T8 , OR2T1 , OR7C2 , OR1L4 , OR1L8 , OR5R1 , OR52I2 , OR2L13 , OR51G2 , OR5T1 , OR7D4 , OR4B1 , OR2S2 , OR5H15 , OR56A4 , OR2V1 , OR4C6 , OR2T35 , OR6B2 , OR51E2 , OR5H2 , OR56A3 , OR10S1 , OR5D14 , OR1Q1 , OR52N2 , OR7A17 , OR2D2 , OR51V1 , OR52B6 , OR2H1 , OR12D3 , OR10A7 , OR2L2 , OR1L6 , OR2J3 , OR2AT4 , OR5D16 , OR8D2 , OR4F4 , OR1D2 , OR1A2 , OR4F6 , OR5P2 , RTP2 , OR4C45 , OR7G2 , REEP1 , OR9K2 , OR4C12 , OR6X1 , OR4N4 , OR2A14 , OR5C1 , OR10G7 , OR4X2 , OR51S1 , OR2T2 , OR51L1 , OR6C74 , OR2K2 , OR5M11 , OR2A5 , OR8H1 , OR13D1 , OR2AG1 , OR5P3 , OR10A3 , OR10H5 , OR10H3 , OR6C65 , OR52K1 , OR56B4 , OR4D2 , EBF1 , OR6T1
Olfactory Signaling Pathway 0.0000000 0.0000000 NA -0.6969532 -2.121207 381 OR6Q1 , OR9I1 , OR1S2 , OR51I1 , OR6P1 , OR10W1 , OR2T29 , OR5H1 , OR4C3 , OR3A2 , OR8B8 , OR5H6 , OR1S1 , OR2B11 , OR14J1 , OR10K2 , OR5B2 , OR10J3 , OR2M7 , OR2M4 , OR1L1 , OR52D1 , OR5AC2 , OR4D1 , OR10C1 , OR56A1 , OR10G8 , OR8H2 , OR10Z1 , OR52A5 , OR2G2 , OR4D10 , OR10G9 , OR5W2 , OR13G1 , OR4D9 , OR8B12 , OR8K3 , OR2T12 , OR5H14 , OR1B1 , OR2T5 , OR5B3 , OR52E2 , OR9Q2 , OR10J1 , OR2M5 , OR5J2 , OR2AP1 , OR4D11 , OR6Y1 , OR6K2 , OR52E6 , OR5B17 , OR5B21 , OR4C16 , OR5B12 , OR9Q1 , OR10J5 , OR6N1 , OR1N1 , OR4E2 , OR10Q1 , OR2L5 , OR51B6 , OR5AP2 , OR8J3 , OR5T2 , OR5AS1 , OR52A1 , OR8U1 , OR51F1 , OR10G4 , OR12D2 , OR5A1 , OR14I1 , OR6N2 , OR8K5 , ANO2 , OR6B1 , OR56B1 , OR4F15 , OR6F1 , OR11A1 , OR5F1 , OR4A15 , OR10A5 , OR51E1 , OR7G3 , OR8B4 , OR5M8 , OR4A16 , OR51I2 , CNGA2 , OR8U8 , OR6C75 , OR2W5 , OR5I1 , OR9G9 , OR9G1 , OR51B5 , OR4D5 , OR4D6 , OR10AG1, OR2F1 , OR2AG2 , OR5T3 , OR5AU1 , OR51T1 , OR51B2 , OR11L1 , OR51F2 , OR5V1 , OR2A25 , OR2G3 , OR52N4 , OR2G6 , OR8J1 , OR8D1 , OR2J2 , OR2L8 , OR2B3 , OR1K1 , OR8A1 , OR5M9 , OR2A12 , OR52J3 , OR52E4 , OR52H1 , OR4C46 , OR4K5 , OR52R1 , OR9G4 , OR1J2 , OR4C15 , OR2T6 , OR2T33 , OR56A5 , OR52L1 , OR5M3 , OR6K6 , OR2M3 , OR8G5 , OR10T2 , OR51A7 , OR10K1 , OR1C1 , OR2Z1 , OR51B4 , OR8H3 , OR8G1 , OR10X1 , OR2W1 , OR2M2 , OR5M1 , OR51Q1 , OR2AE1 , OR2A2 , OR14A16, OR2T34 , OR5AR1 , OR3A3 , OR8I2 , OR51A2 , OR5L1 , OR9A2 , OR51D1 , OR14C36, OR4K13 , OR52B2 , OR1M1 , OR52W1 , OR2A4 , OR52K2 , OR4A47 , OR52N1 , OR10A4 , OR5D13 , OR5D18 , OR4S1 , OR8K1 , OR2Y1 , OR8B2 , OR2T3 , OR5AK2 , OR52E8 , OR2W3 , OR51G1 , OR5L2 , OR5A2 , OR2T8 , OR2T1 , OR7C2 , OR1L4 , OR1L8 , OR5R1 , OR52I2 , OR2L13 , OR51G2 , OR5T1 , OR7D4 , OR4B1 , OR2S2 , OR5H15 , OR56A4 , OR2V1 , OR4C6 , OR2T35 , OR6B2 , OR51E2 , OR5H2 , OR56A3 , OR10S1 , OR5D14 , OR1Q1 , OR52N2 , OR7A17 , OR2D2 , CNGA4 , OR51V1 , OR52B6 , OR2H1 , OR12D3 , OR10A7 , OR2L2 , OR1L6 , OR2J3 , OR2AT4 , OR5D16 , OR8D2 , OR4F4 , OR1D2 , OR1A2 , OR4F6 , OR5P2 , RTP2 , OR4C45 , OR7G2 , REEP1 , OR9K2 , OR4C12 , OR6X1 , OR4N4 , OR2A14 , OR5C1 , OR10G7 , OR4X2 , OR51S1 , OR2T2 , OR51L1 , OR6C74 , OR2K2 , OR5M11 , OR2A5 , OR8H1 , OR13D1 , OR2AG1 , OR5P3 , OR10A3 , OR10H5 , OR10H3 , OR6C65 , OR52K1 , OR56B4 , OR4D2 , EBF1 , OR6T1
Sensory Perception 0.0000000 0.0000000 1.7624393 -0.5992982 -1.832576 597 OR6Q1 , OR9I1 , OR1S2 , OR51I1 , OR6P1 , TAS2R16 , OR10W1 , OR2T29 , OR5H1 , OR4C3 , OR3A2 , OR8B8 , OR5H6 , OR1S1 , TAS2R1 , OR2B11 , OR14J1 , OR10K2 , OR5B2 , OR10J3 , OR2M7 , OR2M4 , OR1L1 , OR52D1 , OR5AC2 , OR4D1 , OR10C1 , OR56A1 , OR10G8 , OR8H2 , OR10Z1 , OR52A5 , OR2G2 , OR4D10 , OR10G9 , OR5W2 , OR13G1 , OR4D9 , OR8B12 , OR8K3 , OR2T12 , OR5H14 , OR1B1 , OR2T5 , OR5B3 , OR52E2 , OR9Q2 , OR10J1 , OR2M5 , OR5J2 , OR2AP1 , OR4D11 , OR6Y1 , OR6K2 , OR52E6 , OR5B17 , OR5B21 , OR4C16 , OR5B12 , OR9Q1 , OR10J5 , OR6N1 , OR1N1 , OR4E2 , OR10Q1 , XIRP2 , OR2L5 , OR51B6 , OR5AP2 , OR8J3 , OR5T2 , GRXCR1 , OR5AS1 , OR52A1 , OR8U1 , OR51F1 , OR10G4 , OR12D2 , OR5A1 , OR14I1 , OR6N2 , OR8K5 , ANO2 , OR6B1 , OR56B1 , OR4F15 , AKR1B10 , OR6F1 , OR11A1 , OR5F1 , OR4A15 , OR10A5 , OR51E1 , OR7G3 , OPN1LW , OR8B4 , OR5M8 , OR4A16 , OR51I2 , CNGA2 , OR8U8 , OR6C75 , OR2W5 , OR5I1 , OR9G9 , OR9G1 , OR51B5 , OR4D5 , OR4D6 , OR10AG1 , OR2F1 , OR2AG2 , OR5T3 , OR5AU1 , OR51T1 , OR51B2 , OR11L1 , OR51F2 , OR5V1 , OR2A25 , OR2G3 , OR52N4 , OR2G6 , OR8J1 , OR8D1 , OR2J2 , OR2L8 , OR2B3 , OR1K1 , OR8A1 , OR5M9 , OR2A12 , OR52J3 , OR52E4 , OR52H1 , GPC5 , OR4C46 , OR4K5 , OR52R1 , OR9G4 , OR1J2 , OR4C15 , OR2T6 , OR2T33 , OR56A5 , APOB , OR52L1 , OR5M3 , OR6K6 , OR2M3 , OR8G5 , OR10T2 , OR51A7 , OR10K1 , OR1C1 , OR2Z1 , OR51B4 , OR8H3 , OR8G1 , OR10X1 , OR2W1 , OR2M2 , OR5M1 , OR51Q1 , OR2AE1 , OR2A2 , OR14A16 , OR2T34 , OR5AR1 , OR3A3 , TAS1R2 , GPC6 , OR8I2 , OR51A2 , SDR9C7 , OR5L1 , OR9A2 , OR51D1 , OR14C36 , OR4K13 , USH1C , OR52B2 , OR1M1 , OR52W1 , OR2A4 , OR52K2 , OR4A47 , OR52N1 , OR10A4 , GUCA1C , OR5D13 , OR5D18 , OR4S1 , OR8K1 , OR2Y1 , OR8B2 , OR2T3 , OR5AK2 , OR52E8 , TAS2R40 , OR2W3 , OR51G1 , OR5L2 , OR5A2 , APOA4 , OR2T8 , OR2T1 , OR7C2 , CAMKMT , PRKCQ , OR1L4 , OR1L8 , OR5R1 , OR52I2 , OR2L13 , OR51G2 , OR5T1 , OR7D4 , OR4B1 , TAS2R41 , RHO , OR2S2 , OR5H15 , OR56A4 , BSN , OR2V1 , OR4C6 , PCDH15 , DHRS9 , OR2T35 , OR6B2 , OR51E2 , OR5H2 , OR56A3 , OR10S1 , OR5D14 , OR1Q1 , AKR1C3 , SDC1 , SCN2A , OR52N2 , OR7A17 , TAS2R8 , OR2D2 , CNGA4 , OR51V1 , OR52B6 , OR2H1 , OR12D3 , OR10A7 , TAS2R39 , OR2L2 , OR1L6 , OR2J3 , OR2AT4 , OR5D16 , OR8D2 , OR4F4 , OR1D2 , PLB1 , OR1A2 , OR4F6 , OR5P2 , TAS2R5 , RTP2 , OR4C45 , SDC3 , OR7G2 , TAS2R46 , REEP1 , TAS2R20 , OR9K2 , OR4C12 , OR6X1 , OR4N4 , OR2A14 , OR5C1 , CACNA2D2, AKR1C1 , OR10G7 , OR4X2 , OR51S1 , OR2T2 , OR51L1 , OR6C74 , OR2K2 , OR5M11 , OR2A5 , TAS2R38 , OR8H1 , OR13D1 , SYP , OR2AG1 , OR5P3 , OR10A3 , OR10H5 , OR10H3 , OR6C65 , RDH12 , TRPM5 , OR52K1 , OR56B4 , OR4D2 , RGS9 , OTOG , EBF1 , OR6T1 , PNLIP , RDH16 , TAS1R3 , OR1L3 , PPEF1 , OR5AN1 , OPN1MW , OR2T27 , OR1E2 , OR8B3 , OPN1SW , OR10V1 , OR2D3 , OR10G2 , NAPEPLD , OR13C2 , OR6C6 , OR7E24 , OR1N2 , OR8D4 , TAS2R30 , OR6C1 , OR6C4 , GRK4 , OR8G2 , OR4F5 , RDH8 , EPS8 , OR51M1 , OR10H4 , FNTB , OR6C2 , OR2T4 , PCLO , ESPNL , OR7G1 , OR6K3 , PLS1 , OR2AK2 , OR11G2 , OR4K15 , OR7D2 , TAS2R3 , OR1J4 , OR2V2 , OR4M1 , OR4X1 , OR10A6 , FAM65B , CDH23 , TTR , OR10P1 , OR10H1 , TAS2R14 , OR2F2 , MYO7A , TAS2R50 , CLIC5
Activation of HOX genes during differentiation 0.0000000 0.0000000 0.9759947 0.6621251 3.013424 63 HOXA3 , HOXD4 , HOXA2 , HOXB1 , PAX6 , HOXC4 , HOXD3 , HOXB3 , HOXA4 , HOXB4 , RARA , MEIS1 , HOXB2 , RARG , POLR2C, HOXD1 , PCGF2 , MAFB
Activation of anterior HOX genes in hindbrain development during early embryogenesis 0.0000000 0.0000000 0.9759947 0.6621251 3.013424 63 HOXA3 , HOXD4 , HOXA2 , HOXB1 , PAX6 , HOXC4 , HOXD3 , HOXB3 , HOXA4 , HOXB4 , RARA , MEIS1 , HOXB2 , RARG , POLR2C, HOXD1 , PCGF2 , MAFB
Transcriptional regulation of pluripotent stem cells 0.0000000 0.0000014 0.7749390 0.7177020 2.826065 31 CDX2 , EPAS1 , GSC , PRDM14, GATA6 , FOXD3 , ZIC3 , EOMES , SALL1 , HIF3A , KLF4 , LIN28A, EPHA1 , SMAD4
Antimicrobial peptides 0.0000000 0.0000134 0.7195128 -0.6099296 -1.746063 85 RNASE6 , RNASE3 , LCN2 , S100A8 , TLR1 , DEFB135 , REG3A , SEMG1 , PI3 , DEFB106A, BPIFA1 , DEFB107A, DEFB118 , DEFB104A, CCR2 , DEFB121 , REG3G , DEFA4 , DEFB119 , DEFB116 , DEFB105A, S100A7A , DEFB127 , DEFB115 , DEFA1 , HTN3 , DEFB125 , DCD , DEFB103A, DEFB126 , DEFB128 , DEFB108B, CCR6 , DEFB133 , PDZD11 , GNLY , DEFA3 , HTN1 , DEFB110 , S100A7 , DEFB114 , DEFB113 , DEFA5 , DEFB131 , DEFB123 , ATOX1 , LTF , BPIFB6 , BPI , ELANE , DEFB129 , LYZ , PLA2G2A , DEFB134 , PGLYRP4 , PRTN3 , BPIFB2 , SLC11A1 , S100A9
Defensins 0.0000003 0.0000808 0.6749629 -0.6933987 -1.871732 41 TLR1 , DEFB135 , DEFB106A, DEFB107A, DEFB118 , DEFB104A, CCR2 , DEFB121 , DEFA4 , DEFB119 , DEFB116 , DEFB105A, DEFB127 , DEFB115 , DEFA1 , DEFB125 , DEFB103A, DEFB126 , DEFB128 , DEFB108B, CCR6 , DEFB133 , DEFA3 , DEFB110 , DEFB114 , DEFB113 , DEFA5 , DEFB131 , DEFB123
Beta defensins 0.0000014 0.0003845 0.6435518 -0.7135024 -1.882162 33 TLR1 , DEFB135 , DEFB106A, DEFB107A, DEFB118 , DEFB104A, CCR2 , DEFB121 , DEFB119 , DEFB116 , DEFB105A, DEFB127 , DEFB115 , DEFB125 , DEFB103A, DEFB126 , DEFB128 , DEFB108B, CCR6 , DEFB133 , DEFB110 , DEFB114 , DEFB113 , DEFB131 , DEFB123
Regulation of beta-cell development 0.0000037 0.0009394 0.6272567 0.5352335 2.288524 42 NKX6-1 , PAX6 , PDX1 , PTF1A , FOXA2 , ONECUT1, NEUROD1, ONECUT3, NKX2-2 , HNF1B , NEUROG3, FGF10 , INSM1
Regulation of gene expression in early pancreatic precursor cells 0.0000049 0.0011353 0.6105269 0.9250498 2.454448 8 NKX6-1 , PDX1 , PTF1A , ONECUT1, ONECUT3, HNF1B , FGF10
Keratinization 0.0000054 0.0011353 0.6105269 -0.4808004 -1.437220 216 CSTA , KRTAP19-8 , KRTAP11-1 , KRT80 , KRTAP6-2 , KRTAP5-2 , KRTAP20-2 , KRTAP6-3 , KRTAP12-4 , KRTAP22-1 , PI3 , KRTAP8-1 , KRT8 , KRT6B , KRTAP12-2 , KRTAP19-5 , KRTAP20-1 , KRTAP13-1 , KRTAP6-1 , KRTAP4-6 , KRTAP5-1 , KRTAP10-8 , KRT26 , KRTAP19-6 , KRT16 , KRTAP19-7 , KRT5 , KRTAP21-1 , KRTAP26-1 , KRTAP12-1 , TGM5 , KRTAP21-2 , CASP14 , KRTAP5-3 , KRTAP21-3 , KRTAP5-8 , DSC1 , DSG3 , KRTAP4-11 , KRT17 , DSP , KRTAP13-2 , KRTAP2-4 , KRT6A , KRTAP19-2 , KRTAP5-11 , KRTAP4-8 , KRTAP10-5 , CDSN , KRTAP24-1 , KRT18 , KRTAP4-5 , KRTAP10-11, LCE1B , KRTAP1-1 , KRTAP15-1 , KRTAP1-3 , LIPM , KRT28 , LCE1F , PKP3 , KRTAP25-1 , KRTAP23-1 , KRTAP9-1 , KRT34 , KRTAP9-3 , KRTAP10-9 , KLK12 , KRTAP9-2 , LIPK , KRTAP19-1 , KRTAP5-7 , KRTAP10-1 , LCE2B , KRTAP19-3 , KRT24 , LCE3D , ST14 , KRTAP10-7 , SPINK9 , KRT14 , KRT37 , KRTAP5-10 , KRTAP13-4 , FLG , KRTAP10-3 , LCE1C , KRT33B , KRT75 , KRT38 , KRT15 , KRTAP9-9 , PERP , KRT31 , SPINK5
Innate Immune System 0.0000065 0.0012644 0.6105269 -0.3944593 -1.212092 1036 IL1B , PTPN6 , RNASE6 , RNASE3 , MAPK13 , TIFA , MNDA , IFNA2 , ZBP1 , LCN2 , CD300E , LILRB2 , SIRPB1 , S100A8 , CD68 , CD300LB , FCER1A , SIGLEC14 , MS4A3 , LAIR1 , CLEC4E , PKM , MUC19 , CRP , TLR1 , AOC1 , RNASE2 , FCN1 , ADGRG3 , TCN1 , DEFB135 , REG3A , SEMG1 , PI3 , CYBB , DEFB106A , AIM2 , CXCR1 , BPIFA1 , TMC6 , NLRP4 , IRAK1 , CLEC4D , TARM1 , DEFB107A , MUC7 , C4A , VNN1 , ALDOA , DEFB118 , C4B , DEFB104A , C6 , CLEC4A , CCR2 , FCGR3B , CEACAM3 , DEFB121 , NCF4 , CD33 , REG3G , DEFA4 , HBB , PIK3C3 , HP , LRRC7 , GPR84 , CPPED1 , LCP2 , TLR6 , CD209 , DEFB119 , DEFB116 , CXCR2 , NLRP3 , PLD1 , PSEN1 , FCAR , APOB , PSMF1 , HGSNAT , DEFB105A , S100A7A , IFNA14 , PANX1 , LYN , DEFB127 , TLR9 , IKBKE , BCL2 , CCL22 , DEFB115 , CLEC5A , DSC1 , GLIPR1 , MCEMP1 , LAT2 , AZU1 , KIR2DS4 , FCGR3A , CEACAM8 , DEFA1 , PSMB11 , PAK1 , HTN3 , IFNA21 , ATP6V0D2 , CD53 , DEFB125 , DOCK1 , DCD , MUC13 , DSP , CNN2 , PTPRN2 , PRG2 , PRKCQ , MUC5B , COMMD9 , MBL2 , DEFB103A , FTH1 , AMPD3 , DEFB126 , HRAS , PTPRJ , CLEC7A , DEFB128 , GRB2 , SAA1 , CPB2 , OLFM4 , TLR7 , SIGLEC16 , PLAC8 , DEFB108B , NME2 , CCR6 , FPR2 , BTRC , PELI2 , TLR4 , DEFB133 , MASP2 , TNFAIP6 , CRISP3 , C8A , TEC , CR2 , FCGR2A , MUC15 , MAP2K6 , MUC5AC , UNC93B1 , CLEC6A , RAB10 , PDZD11 , CALML5 , LAMTOR3 , GCA , IFNA16 , DNASE1L1 , ITK , FCGR1A , MAP2K3 , DEGS1 , ATP8A1 , GNLY , CTSZ , TKFC , SELL , C6orf120 , IFNA1 , PRG3 , C3AR1 , NCKAP1L , DEFA3 , HTN1 , WASF3 , MIF , DBNL , RNF125 , DEFB110 , CTSS , S100A7 , PSMD6 , DEFB114 , C1QC , HEXB , FPR1 , CAB39 , ATP6V0B , DEFB113 , NCR2 , DEFA5 , SIGLEC5 , LRG1 , RAB31 , BRK1 , PTGES2 , MUC21 , CD180 , MUC6 , C8B , IFNA8 , DEFB131 , TREM2 , GALNS , MGAM , PIK3CB , SOCS1 , MUC2 , S100P , GDI2 , UBE2D1 , MAP3K7 , CD58 , DOK3 , COTL1 , PSMD9 , PSMB7 , CPNE3 , DNM3 , S100A11 , RPS6KA2 , DEFB123 , MUC17 , PRKDC , CEP290 , TAB3 , ATOX1 , LTF , BIN2 , CFHR2 , ITPR2 , PTPRC , VAV3 , MALT1 , BPIFB6 , GSTP1 , RAB44 , CHIT1 , BPI , FRMPD3 , LILRA3 , STK11IP , IFNB1 , ADGRE3 , C9 , IFNA10 , POLR2F , CEACAM1 , CNPY3 , HSPA8 , PSMC5 , IFNA7 , ELANE , BTK , ADAM8 , PROS1 , RAB24 , DHX36 , DEFB129 , PECAM1 , UBE2L6 , LYZ , KCMF1 , PSAP , UNC13D , PLA2G2A , ACTR3 , TNIP2 , MUCL1 , ACTR1B , DEFB134 , TAB2 , PDAP1 , IGF2R , TTR , HMOX2 , S100A12 , NOS2 , MASP1 , BCL10 , C1QA , LBP , ATG5 , FGB , PRKACB , TLR8 , IRAK4 , SYNGR1 , ELMO1 , ARMC8 , MMP8 , PGLYRP4 , PSMD14 , DNAJC3 , RETN , PADI2 , IQGAP2 , PRTN3 , HRNR , PTPN11 , BPIFB2 , SLC15A4 , IFNA6 , TRIM4 , LILRB3 , IKBKG , SLC11A1 , S100A9 , PRKACG , HK3 , PLCG2 , MAPK8 , GRN , ITPR1 , CFHR3 , MUC16 , NCF2 , APRT , ATP6V1G3 , PSMD2 , C8G , CAND1 , RNASE7 , DHX9 , CYFIP2 , RAB9B , BPIFA2 , COLEC10 , ABI1 , IRAK2 , CLEC12A , ATP8B4 , FGA , PA2G4 , HSP90AA1 , MEF2C , GGH , TRPM2 , CHRNB4 , GM2A , DYNLL1 , IFI16 , CFHR5 , ARG1 , MGST1 , CYFIP1 , RAB14 , RAB3D , LY86 , SERPINB10, RPS6KA1 , DDOST , RAB7A , HSPA6 , TRAF6 , MYH2 , TIMP2 , MPO , ART1 , TOM1 , ITGB2 , CHI3L1 , MAPKAPK2 , NLRP1 , MS4A2 , CASP1 , LPO , TLR3 , FLG2 , QSOX1 , IDH1 , ATP6V0A2 , CPN2 , GAB2 , PRKCSH , UBE2D3 , CHUK , ITGAX , APEH , RIPK3 , PLD3 , COMMD3 , QPCT , SERPINB3 , BIRC2 , OLR1 , ATP6V1C2 , ATP6V1C1 , NOD2 , CLEC4C , CAMP , POLR3K , POLR3A , ATP6V1G1 , CTSD , CTSG , CDA , CD247 , CTSB , PAK3 , UBA52 , GPI , PAK2 , LPCAT1 , DEFB132 , NLRC3 , PSME4 , ERP44 , PPIA , MAVS , KLRC2 , CFI , MAP2K4 , POLR3C , CFH , SERPINA3 , MUC20 , NKIRAS2 , RAB37 , RNF216 , PSMB2 , LY96 , EPPIN , LRRC14 , POLR3G , POLR3D , CAT , CREG1 , BPIFB1 , PGAM1 , PLA2G6 , C1QB , IFNA4 , JUP , ATP6V1F , NCSTN , PTAFR , P2RX1 , PPBP , CRACR2A , IRAK3 , S100B , MAPKAPK3 , CTSC , MAPK11 , DEFB136 , POLR3B , EEA1 , TRAF2 , DEFB124 , PRKCD , EEF2 , MEFV , SURF4 , C7 , ATF1 , TUBB , PSMA2 , SLCO4C1 , SYK , NFATC1 , ATP11B , ATP6V1H , CPNE1 , RNASET2 , NLRC4 , GUSB , FABP5 , ATP6V1G2 , NFATC2 , DNM1 , RPS27A , C5AR2 , BIRC3 , C5 , RAB18 , UBE2V1 , AGL , GYG1 , TBC1D10C , ITLN1 , ARSB , ITCH , PRDX6 , CAPN1
Regulation of gene expression in beta cells 0.0001090 0.0197955 0.5384341 0.6111664 2.190232 21 NKX6-1 , PAX6 , PDX1 , FOXA2 , NEUROD1, NKX2-2
POU5F1 (OCT4), SOX2, NANOG repress genes related to differentiation 0.0001867 0.0316495 0.5188481 0.8153356 2.331023 10 CDX2 , GSC , GATA6, EOMES, HHEX
Signaling by BMP 0.0004333 0.0688632 0.4984931 0.4921992 1.849614 28 SMAD6 , SMAD7 , ACVRL1, SMURF2, SKI , BMP2 , NOG , BMPR2 , BMPR1A
Immune System 0.0006182 0.0924792 0.4772708 -0.3625402 -1.122448 1937 IL1B , PTPN6 , RNASE6 , RNASE3 , MAPK13 , TIFA , LCP1 , MNDA , IFNA2 , EIF4E , ZNRF2 , ZBP1 , HIF1A , IL22RA2 , LCN2 , CD300E , LILRB2 , IL1A , AP1S1 , SIRPB1 , S100A8 , CD68 , KIF2B , LNX1 , CD300LB , FCER1A , SIGLEC14 , MS4A3 , LAIR1 , LILRA1 , CLEC4E , HLA-DRA , PKM , MUC19 , CRP , CD80 , TLR1 , LILRA2 , AOC1 , HLA-DMB , HLA-DOB , HAVCR2 , RNASE2 , FCN1 , CD79A , LGALS9 , OASL , FBXL7 , ADGRG3 , ASB12 , IL3 , TCN1 , IL18RAP , BATF , DEFB135 , KIF4B , REG3A , CD1C , CD300LF , SEMG1 , PI3 , TREML2 , CYBB , LAIR2 , DEFB106A , AIM2 , CXCR1 , BPIFA1 , IL23A , TMC6 , NLRP4 , IRAK1 , CLEC4D , CRTAM , SLAMF6 , CCL11 , LILRA4 , TARM1 , DEFB107A , KIF4A , IL31RA , MIB2 , MUC7 , KPNA1 , C4A , VHL , AKT3 , VNN1 , CCL3 , ALDOA , DEFB118 , TNF , PRLR , C4B , DEFB104A , C6 , FYB , CLEC4A , CD40LG , DAPP1 , CCR2 , FCGR3B , CEACAM3 , DEFB121 , NCF4 , CTLA4 , STAT4 , SIGLEC6 , LILRB4 , CIITA , CD33 , REG3G , IL18R1 , DEFA4 , HBB , PIK3C3 , KLHL20 , HP , DET1 , LRRC7 , GPR84 , CPPED1 , LCP2 , TLR6 , CD209 , IL17A , DEFB119 , IL10 , RNF115 , SIGLEC12 , DEFB116 , CXCR2 , NLRP3 , HACE1 , PLD1 , PSEN1 , SLA , FCAR , APOB , PSMF1 , HGSNAT , IL16 , KIR3DL2 , DEFB105A , S100A7A , IFNA14 , CCL19 , PANX1 , KIR3DL1 , LYN , IL20RA , KIR2DL4 , DEFB127 , IL13RA2 , TLR9 , IKBKE , FCER2 , BCL2 , CCL22 , KIR2DL3 , DCTN5 , DEFB115 , BTLA , CLEC5A , DSC1 , EDARADD , CD22 , GLIPR1 , MCEMP1 , LAT2 , AZU1 , CD300LD , KIR2DS4 , PILRB , IL17F , FCGR3A , CEACAM8 , DEFA1 , EIF4A2 , PSMB11 , IL1RL2 , PAK1 , HTN3 , IFNA21 , ATP6V0D2 , CD53 , DEFB125 , DOCK1 , CBLB , FCGR1B , DCD , MUC13 , DSP , CNN2 , PTPRN2 , PRG2 , PRKCQ , CSF1R , TNFRSF13C, PTPN14 , MUC5B , PTPN22 , COMMD9 , MBL2 , DEFB103A , MRC1 , FTH1 , AMPD3 , DEFB126 , HRAS , PTPRJ , CLEC7A , IL1RAP , DEFB128 , GRB2 , SAA1 , CPB2 , OLFM4 , TLR7 , SIGLEC16 , PLAC8 , DEFB108B , NME2 , CCR6 , TRIM29 , IL18 , FPR2 , AIP , BTRC , PELI2 , TLR4 , CD1D , IL1RL1 , ASB10 , SDC1 , TRIM48 , DEFB133 , MASP2 , CD79B , TNFRSF13B, TNFAIP6 , HLA-DOA , RAG1 , ICOS , CRISP3 , C8A , TEC , CD1A , CR2 , FCGR2A , RNF217 , MUC15 , CD1B , MAP2K6 , ORAI2 , KIF15 , CCR5 , MUC5AC , TRIM34 , IL36G , UNC93B1 , IL37 , CLEC6A , TRIM2 , FLNB , GLYCAM1 , RAB10 , PDZD11 , SIAH2 , CALML5 , CCR1 , IL2RA , LAMTOR3 , SIGLEC10 , SIGLEC8 , GCA , IFNA16 , DNASE1L1 , PTK2B , KBTBD8 , ITK , HLA-DQA2 , FCGR1A , MAP2K3 , PARK2 , IL1RN , DEGS1 , EIF4E2 , ASB8 , PAG1 , UBE2V2 , UBE2U , HLA-DQA1 , ATP8A1 , GNLY , CTSZ , TKFC , ANXA1 , SELL , C6orf120 , IFNA1 , PRG3 , C3AR1 , NCKAP1L , DEFA3 , HTN1 , BLK , CDKN1A , WASF3 , MIF , DBNL , RNF125 , DEFB110 , CTSS , ASB11 , S100A7 , PSMD6 , DEFB114 , C1QC , CSH1 , HEXB , FPR1 , ANAPC4 , RNF130 , IL21R , CAB39 , ATP6V0B , DEFB113 , NCR2 , DEFA5 , ISG20 , IL20RB , SIGLEC5 , LRG1 , RAB31 , BRK1 , PTGES2 , MUC21 , CD180 , MUC6 , IL15 , C8B , IFNA8 , DEFB131 , TREM2 , KIF26A , GALNS , MGAM , PIK3CB , NUP133 , SOCS1 , MUC2 , IL17RA , S100P , ASB15 , SH3GL2 , GDI2 , UBE2D1 , TNFRSF9 , UBE4A , MAP3K7 , CD58 , LILRB1 , DOK3 , COTL1 , FBXW9 , PSMD9 , PSMB7 , CPNE3 , DNM3 , CD28 , KIR2DL1 , S100A11 , MRC2 , RPS6KA2 , STIM1 , DEFB123 , EIF2AK2 , MUC17 , FBXO10 , PRKDC , SPSB1 , CEP290 , KLRF1 , KLHL25 , TAB3 , ATOX1 , TRAT1 , CCL4 , CA1 , LTF , BIN2 , NFKBIE , CFHR2 , ITPR2 , POU2F1 , RASGRP3 , PTPRC , VAV3 , KIF5C , MALT1 , BPIFB6 , GSTP1 , LILRA6 , TRIM10 , IL12B , RAB44 , CHIT1 , SERPINB2 , IL36B , RNASEL , BPI , STX4 , FRMPD3 , LILRA3 , STK11IP , FBXO32 , IFNB1 , ADGRE3 , UBE2E2 , C9 , IFNA10 , CANX , POLR2F , CEACAM1 , CNPY3 , HSPA8 , PSMC5 , NUP37 , EIF4A1 , IFNA7 , ELANE , ZBTB16 , BTK , RORA , ADAM8 , EDAR , PROS1 , TNFSF13B , TNFRSF17 , RAB24 , DHX36 , CD207 , DEFB129 , PECAM1 , IL22 , CSK , UBE2F , UBE2L6 , LYZ , KCMF1 , TREML1 , PSAP , RNF114 , UNC13D , SIGLEC7 , LTN1 , ICOSLG , PLA2G2A , IL17C , ACTR3 , TNIP2 , IL1R2 , MUCL1 , ACTR1B , DEFB134 , CD86 , TRIM62 , SH3KBP1 , NUP43 , F13A1 , TAB2 , TNFSF8 , PDAP1 , IGF2R , TTR , HMOX2 , S100A12 , MMP3 , FBXL13 , KLRC1 , CTSF , EVL , NOS2 , UBE2L3 , MASP1 , BCL10 , CDC16 , UNKL , C1QA , OPRM1 , LBP , ATG5 , FGB , PRKACB , TLR8 , PRKCB , IRAK4 , SYNGR1 , ELMO1 , UBE2D4 , ARMC8 , TRIM68 , MMP8 , PGLYRP4 , PSMD14 , DNAJC3 , RETN , IFNL3 , PADI2 , IQGAP2 , PRTN3 , KIFAP3 , HRNR , PTPN11 , MLST8 , BPIFB2 , RSAD2 , CD300C , OSM , PDCD1LG2 , SLC15A4 , HGF , TREML4 , IFNL1 , IFNA6 , TRIM4 , SOD1 , UBOX5 , LILRB3 , IKBKG , SLC11A1 , GBP2 , FBXO27 , S100A9 , PRKACG , HK3 , PLCG2 , MAPK8 , GRN , ITPR1 , CFHR3 , LONRF1 , MUC16 , NCF2 , EBI3 , APRT , ATP6V1G3 , UBE2Q2 , LILRA5 , TNFSF15 , PSMD2 , ASB17 , TRIM9 , C8G , CAND1 , TRIM39 , IRF8 , ASB18 , TRIM41 , BCL2L11 , RNASE7 , DHX9 , PRKG1 , HECW2 , CYFIP2 , CD101 , SH2D1B , HSPA9 , NEDD4 , RAB9B , BPIFA2 , COLEC10 , PTPN2 , SIGLEC1 , BTNL2 , MX2 , ABI1 , CD160 , IRAK2 , IL5 , CLEC12A , ATP8B4 , OSBPL1A , LTA , FGA , PA2G4 , HSP90AA1 , MEF2C , GGH , KLRG1 , TRPM2 , CHRNB4 , GM2A , DYNLL1 , OAS3 , IL1RAPL1 , IFI16 , NUP62 , CFHR5 , NUP98 , PTPN18 , LILRB5 , ARG1 , SIGLEC11 , MGST1 , CYFIP1 , RAB14 , TRIM35 , RAB3D , LY86 , BTN3A2 , NDC1 , IL10RA , ZEB1 , SERPINB10, RPS6KA1 , DDOST , SEC24A , RAB7A , IL19 , HSPA6 , TRAF6 , MYH2 , TALDO1 , XDH , TIMP2 , FBXW5 , NCR3 , KPNA5 , MPO , ART1 , TRIM37 , KLHL42 , TOM1 , ITGB2 , GH2 , CHI3L1 , CLEC2D , MAPKAPK2 , GBP5 , NLRP1 , PDE12 , MS4A2 , IRF6 , CASP1 , LPO , ASB1 , TLR3 , KIF23 , NUP160 , FLG2 , QSOX1 , IDH1 , ATP6V0A2 , CPN2 , GAB2 , PRKCSH , GAN , UBE2D3 , CHUK , ITGAX , APEH , UBE2Z , TRIM22 , RIPK3 , PLD3 , COMMD3 , QPCT , SERPINB3 , SAR1B , BIRC2 , IL6R , OLR1 , SH2B1 , ATP6V1C2 , ATP6V1C1 , NOD2 , STUB1 , TRIM14 , CLEC4C , CAMP , SMAD3 , CAPZA3 , UBE2C , POLR3K , SH2D1A , POLR3A , ATP6V1G1 , TRIB3 , CTSD , CTSG , CDA , CD247 , CTSB , PAK3 , UBA52 , GPI , PAK2 , LPCAT1 , DEFB132 , NLRC3 , FBXO7 , PSME4 , NCAM1 , RNF19B , ERP44 , RORC , IL8 , PPIA , EDA2R , UFL1 , RNF34 , MAVS , KLRC2 , CFI , LTB , YWHAZ , MAP2K4 , POLR3C , ANAPC11 , TRIM50 , GBP4 , DYNC1I2 , ANAPC10 , CFH , GRB10 , SERPINA3 , AREL1 , TRIM38 , MUC20 , IL24 , NKIRAS2 , CD96 , RAB37 , RNF216 , SLAMF7 , IL7R , PSMB2 , LY96 , EPPIN , ZAP70 , LRRC14 , ABCE1 , POLR3G , DCTN3 , POLR3D , CAT , CREG1 , BPIFB1 , PGAM1 , PLA2G6 , C1QB , IFNA4 , JUP , ATP6V1F , ASB9 , RBCK1 , NCSTN , PTAFR , P2RX1 , ANAPC1 , PPBP , JAK2 , CRACR2A , SPTBN2 , IRAK3 , S100B , CDC27 , OAS2 , ASB13 , LNPEP , MAPKAPK3 , NCR3LG1 , CTSC , MAPK11 , TNFSF11 , DEFB136 , POLR3B , EEA1 , HLA-DMA , TRAF2 , DEFB124 , CALR , MTAP , CD274 , PRKCD , EEF2 , IFITM1 , MEFV , HSPA5 , RNF138 , TNFRSF12A, SURF4 , C7 , RNF126 , ATF1 , TUBB , PSMA2 , SLCO4C1 , SYK , NFATC1 , FBXO9 , RAE1 , ATP11B , STX1A , KIF2A , IL5RA , ATP6V1H , CPNE1 , RNASET2 , IFI30 , NLRC4 , GUSB , IL20 , CDC23 , UBA6 , BRWD1 , FABP5 , GHR , TNFSF14 , ATP6V1G2 , NFATC2 , DNM1 , RPS27A , C5AR2 , BIRC3 , IFNAR2 , PIK3AP1 , CAMK2D , C5 , IL21 , CSF2RB , SEC24B , RAB18 , UBE2V1 , AGL , GYG1 , TBC1D10C , ITLN1 , ARSB , ITCH , PRDX6 , ASB5 , CAPN1 , FZR1 , SEC31A , WSB1 , GAA , CFHR4 , C5AR1 , RAET1E , CD226 , EIF4G3 , TRIM11 , VAV1 , EPX
Termination of O-glycan biosynthesis 0.0008507 0.1201837 0.4772708 -0.6497671 -1.653451 25 MUC19 , ST6GALNAC3, MUC7 , ST3GAL4 , MUC13 , MUC5B , ST3GAL3 , MUC15 , MUC5AC , MUC21 , MUC6 , MUC2 , MUC17 , MUCL1 , ST6GALNAC2, ST6GAL1 , MUC16
Interleukin-10 signaling 0.0013095 0.1752608 0.4550599 -0.5596367 -1.524391 46 IL1B , IL1A , CD80 , CCL3 , TNF , CCR2 , IL10 , CCL19, FCER2, CCL22, IL18 , CCR5 , CCR1 , IL1RN, FPR1 , CCL4 , IL12B, IL1R2, CD86
Defective SLC2A1 causes GLUT1 deficiency syndrome 1 (GLUT1DS1) 0.0014410 0.1832190 0.4550599 -0.9994518 -1.341253 1 SLC2A1 
stat2 <- sign(as.numeric(factor(fry_res2$Direction))-1.5)  * -log10(fry_res2$PValue)
stat2[is.na(stat2)] <- 0
names(stat2) <- rownames(fry_res2)
fres2 <- fgseaMultilevel(pathways=genesets,stats=stat2)
## Warning in preparePathwaysAndStats(pathways, stats, minSize, maxSize, gseaParam, : There are ties in the preranked stats (6% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.
fres2 <- fres2[order(fres2$pval),]
head(fres2,20)  %>%
  kbl(caption="Promoter fry + fgsea Reactome results") %>%
  kable_styling(full_width=FALSE)
Promoter fry + fgsea Reactome results
pathway pval padj log2err ES NES size leadingEdge
Regulation of PTEN mRNA translation 0.0000223 0.0494497 0.5756103 -0.9008370 -1.781986 13 MIR20A , MIR19B1, MIR19A , MIR17 , AGO2
Competing endogenous RNAs (ceRNAs) regulate PTEN translation 0.0000427 0.0494497 0.5573322 -0.9025228 -1.761460 12 MIR20A , MIR19B1, MIR19A , MIR17 , AGO2
Metabolism 0.0001734 0.1337848 0.5188481 -0.4425252 -1.188388 1299 TSTD1 , GNA15 , ATIC , GNG7 , ACSM3 , SLC2A1 , GLIPR1 , PEX11A , NME2 , NADK , TYMP , MTHFD2 , PARP4 , PGM1 , CACNA2D2 , GGT1 , GLCE , ALOX5AP , FAAH2 , ENO1 , ZDHHC21 , FUT7 , PHGDH , NAT1 , PKM , PANK4 , SLC23A1 , CNDP2 , ALDOA , NDUFAF3 , ACOXL , PIP4K2C , RPS3A , GNG4 , HS6ST1 , SBF1 , SCO2 , AMPD2 , LIPT2 , PSMD6 , PSMD9 , NDUFA12 , PARP10 , SC5D , PRKAG2 , FUT4 , HACD4 , DCTPP1 , HPD , ASNS , AHR , VAC14 , PAOX , LRP8 , B4GALT2 , MCCC2 , RPL17 , ELOVL5 , AIP , PIP4K2A , ABHD5 , HMGCL , NUDT1 , GDPD5 , SLC22A5 , RPS2 , SLC19A1 , PDZD11 , IDS , SHMT2 , KCNJ11 , RPS8 , TSPO , OSBPL2 , MED10 , CHPF , TYMS , PSTK , ACSF3 , RPL13 , TNFAIP8L2 , NOS3 , GPI , DGAT2 , AGPAT3 , RAP1A , PIP5K1C , VAPB , COX6C , MTHFS , RPL3 , SLC37A4 , NUP133 , NUDT4 , NDUFAF6 , CCNC , TKT , SLC35B3 , RPL13A , RPS20 , TK1 , AFMID , MED4 , ACSM1 , NCOA6 , CA6 , PITPNM1 , GCH1 , NDUFA4 , OSBPL9 , FUT10 , NR1H2 , PTGES2 , PSMC5 , PGAM1 , PLEKHA3 , ITPKC , CSGALNACT2, PSMB7 , PI4K2B , NDUFA13 , D2HGDH , NUP43 , MECR , RRM2 , MTMR6 , DECR2 , PPA1 , CAD , DEGS1 , SQRDL , MED31 , ESRRA , ADA , PLCD3 , STARD3 , RPS15 , GPS2 , RAB14 , HMOX2 , NRF1 , INSIG2 , AGMAT , RNLS , TMLHE , SIN3B , SPTLC3 , SLC51A , PPT1 , IP6K1 , CPNE3 , PFKFB2 , APOA5 , CACNA1C , BLVRB , B3GNT7 , KMO , NT5C3A , CTPS1 , TRMT112 , TNFAIP8 , ACP6 , OSBPL3 , PECR , PYCRL , MMADHC , LPIN1 , CBR3 , NUP62 , NUDT19 , PSMA7 , MAN2C1 , ITPR3 , SERINC4 , PDP2 , PNP , RPLP1 , NMRAL1 , LHPP , ARNT , TBL1XR1 , FXN , SCAP , NT5C , PARP6 , ADCY7 , NDUFS7 , HAGH , FAHD1 , MED27 , SARDH , NFYC , PTPMT1 , ABHD3 , COX19 , SURF1 , GLO1 , ARSB , B4GALT4 , RPL9 , LIAS , RPL18A , MTHFD1L , RPS11 , OAT , THTPA , PARP16 , HSD17B1 , OAZ1 , GGCT , CSNK1G2 , ADSL , RPS7 , PPP2CB , PNPLA4 , AGPAT2 , GAPDH , STARD10 , AGPS , TALDO1 , NDUFA6 , SLC16A3 , ECI1 , PDSS1 , CHP1 , LIPT1 , NT5C2 , RPSA , LDHA , GCLC , NDUFAF1 , UQCRFS1 , ADO , GNG5 , NUDT7 , SLC25A32 , COQ2 , CMBL , SMPD2 , ENTPD6 , RPS5 , AMD1 , PYCR2 , MAT2A , HK2 , NDUFB10 , IDI1 , PSMD14 , MPC2 , COX6A1 , SLC25A12 , MTR , UST , CRLS1 , INPP4A , PSMD11 , AKR1A1 , GSTA4 , SLC25A19 , ARF3 , COX10 , UCK2 , HMGCR , XYLB , RPL36 , LYPLA1 , SDC4 , GNG2 , MED24 , GCLM , PLB1 , MOCS2 , CHST14 , FITM2 , SREBF2 , RPS19 , CDK8 , PLEKHA8 , RPS18 , MCAT , ACBD4 , SLC7A5 , PSAT1 , ACOX1 , DCK , MMAA , HIBADH , IMPA1 , ESYT2 , MED21 , EBP , NDUFB4 , ARSA , SUMF1 , RPS4X , RPS26 , INPP1 , BPHL , ACP5 , ADK , FAM120B , CARNMT1 , NAGLU , PSMB3 , GDPD1 , BPNT1 , FABP5 , ADSSL1 , PRKACB , IQGAP1 , PLCG2 , IP6K2 , OGDH , TM7SF2 , ISCU , SHMT1 , IPPK , RPL38 , RPL29 , ETFA , ENTPD7 , CBR4 , RORA , B3GALT4 , NUP210 , XYLT1 , SACM1L , NDUFAB1 , ARG2 , QPRT , SGPL1 , PLEKHA6 , HMMR , VDAC1 , SDHB , RPS3 , PGD , NDUFC1 , PGM2 , B4GALT6 , ECSIT , SP1 , CHAC2 , ACAA1 , GCHFR , RPE , IL4I1 , VDR , EEFSEC , CARNS1 , CDS2 , NAMPT
Translation 0.0010043 0.5809628 0.4550599 -0.5176520 -1.365294 246 EIF4E , AARS2 , MTIF2 , MRPL53 , RPS3A , APEH , RPL17 , MRPL15 , RPS2 , RPS8 , EIF3M , RPL13 , MRPL33 , TRAM1 , RPL3 , MRPL11 , RPL13A , RPS20 , MRPL24 , SRPRB , EARS2 , PPA1 , RPS15 , ETF1 , TRMT112 , EIF4EBP1, MRPL48 , EIF4G1 , RPLP1 , MRPL50 , SEC11C , EIF3H , CARS2 , WARS2 , MRPS14 , MRPL45 , RPL9 , RPL18A , RPS11 , RPS7 , EIF3F , MRPL16 , RPSA , RPS5 , SRP72 , SRP68 , MRPS22 , MRPL27 , EIF3J , MRPS25 , RPL36 , RPS19 , RPS18 , EEF2 , RPS4X , RPS26 , GFM2 , MRPL37 , EIF2B2 , RPL38 , MRPL54 , RPL29 , SRP19 , RPS3 , EIF4A2 , DARS2 , FARSA , RPL36AL , EIF4A1 , SSR3 , SARS2 , MRPS12 , TUFM , RPL28 , MRPL38 , EIF4H , RPL12 , MRPL13 , MRPS17 , RPL7 , MRPL20 , EEF1E1 , MRPL51 , RPL26 , MTFMT , MRPL9 , MRPL34 , RPS23
Endosomal/Vacuolar pathway 0.0019193 0.6017211 0.4550599 0.8083218 1.952307 11 HLA-B, HLA-F, HLA-C, HLA-A, HLA-H, CTSL , CTSV , CTSS
RUNX3 regulates CDKN1A transcription 0.0023385 0.6017211 0.4317077 0.8769222 1.827158 7 SMAD4, RUNX3, ZFHX3
Paracetamol ADME 0.0024712 0.6017211 0.4317077 -0.8796273 -1.622467 9 GGT1 , NAT1 , CNDP2
Sema4D in semaphorin signaling 0.0025679 0.6017211 0.4317077 0.7345359 1.916170 15 RHOB , LIMK1 , ARHGEF12, LIMK2 , RAC1 , RND1 , MYL6
RUNX2 regulates bone development 0.0026657 0.6017211 0.4317077 0.7067518 1.958009 19 MAF , SMAD4, SMAD1, RB1 , SRC
Sema4D induced cell migration and growth-cone collapse 0.0036397 0.6017211 0.4317077 0.7667386 1.893628 12 RHOB , LIMK1 , ARHGEF12, LIMK2 , RND1 , MYL6
NCAM1 interactions 0.0037443 0.6017211 0.4317077 -0.8697495 -1.604247 9 CACNA1S, NRTN , PRNP , CACNA1C
Antigen Presentation: Folding, assembly and peptide loading of class I MHC 0.0037506 0.6017211 0.4317077 0.5870196 1.718866 26 HLA-B , SEC23A, HLA-F , HLA-C , HLA-A , SEC24C, HLA-H , ERAP2 , PDIA3
rRNA processing in the nucleus and cytosol 0.0040813 0.6017211 0.4070179 -0.5209408 -1.350520 166 RPS3A , RPL17 , ISG20L2 , RPS2 , RPS8 , RPL13 , SNU13 , RPL3 , RPL13A , RPS20 , RRP9 , FTSJ3 , RBM28 , ERI1 , RPP38 , RPS15 , WDR3 , TRMT112 , DDX47 , WDR36 , RPLP1 , RPP21 , RPL9 , RPL18A , RPS11 , RCL1 , RPS7 , RRP7A , RPSA , WDR18 , DCAF13 , RPS5 , MPHOSPH6, DDX52 , RIOK3 , RPL36 , RPS19 , RPS18 , NOP14 , RPS4X , RPS26 , RPL38 , RPL29 , DKC1 , RPS3 , BMS1 , RPL36AL , RPL28 , NOP2 , IMP3 , THUMPD1 , RPL12 , RPL7 , UTP3 , RPL26 , RPS23 , RPL18 , GAR1 , NOC4L , RPL14 , PES1 , RPL36A , DDX49 , EXOSC7 , WDR43 , FBL , CSNK1E , RRP1 , RPL11 , KRR1 , LTV1 , CSNK1D , NHP2
rRNA processing 0.0054986 0.6017211 0.4070179 -0.5195811 -1.347972 172 RPS3A , RPL17 , ISG20L2 , RPS2 , RPS8 , RPL13 , SNU13 , RPL3 , RPL13A , RPS20 , RRP9 , FTSJ3 , RBM28 , ERI1 , RPP38 , MTERF4 , RPS15 , WDR3 , TRMT112 , DDX47 , WDR36 , RPLP1 , RPP21 , RPL9 , RPL18A , RPS11 , RCL1 , RPS7 , RRP7A , RPSA , WDR18 , DCAF13 , RPS5 , MPHOSPH6, DDX52 , RIOK3 , RPL36 , RPS19 , RPS18 , NOP14 , RPS4X , RPS26 , RPL38 , RPL29 , DKC1 , RPS3 , BMS1 , RPL36AL , RPL28 , NOP2 , IMP3 , THUMPD1 , RPL12 , RPL7 , UTP3 , RPL26 , RPS23 , RPL18 , GAR1 , NOC4L , RPL14 , PES1 , RPL36A , DDX49 , EXOSC7 , WDR43 , FBL , CSNK1E , RRP1 , RPL11 , KRR1 , LTV1 , CSNK1D , NHP2
Metabolism of amino acids and derivatives 0.0058432 0.6017211 0.4070179 -0.4965521 -1.307011 235 TSTD1 , PHGDH , RPS3A , LIPT2 , PSMD6 , PSMD9 , HPD , ASNS , PAOX , MCCC2 , RPL17 , RPS2 , RPS8 , PSTK , RPL13 , RPL3 , RPL13A , RPS20 , AFMID , PSMC5 , PSMB7 , SQRDL , RPS15 , AGMAT , TMLHE , KMO , PYCRL , PSMA7 , SERINC4 , RPLP1 , NMRAL1 , SARDH , RPL9 , LIAS , RPL18A , RPS11 , OAT , OAZ1 , RPS7 , LIPT1 , RPSA , ADO , RPS5 , AMD1 , PYCR2 , PSMD14 , SLC25A12, MTR , PSMD11 , RPL36 , RPS19 , RPS18 , SLC7A5 , PSAT1 , HIBADH , RPS4X , RPS26 , CARNMT1 , PSMB3 , OGDH , SHMT1 , RPL38 , RPL29 , NDUFAB1 , ARG2 , RPS3 , IL4I1 , EEFSEC , CARNS1 , RPL36AL , RPL28 , PHYKPL , RPL12 , RPL7 , PSMB8 , PSME4 , ENOPH1 , EEF1E1 , RPL26 , AZIN1 , OAZ3 , RPS23 , RPL18 , SEPHS2 , PAPSS1 , PSMA2 , RPL14 , SLC25A15
Eukaryotic Translation Termination 0.0058705 0.6017211 0.4070179 -0.5854830 -1.463322 77 RPS3A , APEH , RPL17 , RPS2 , RPS8 , RPL13 , RPL3 , RPL13A , RPS20 , RPS15 , ETF1 , TRMT112, RPLP1 , RPL9 , RPL18A , RPS11 , RPS7 , RPSA , RPS5 , RPL36 , RPS19 , RPS18 , RPS4X , RPS26 , RPL38 , RPL29 , RPS3 , RPL36AL, RPL28 , RPL12 , RPL7 , RPL26 , RPS23 , RPL18 , N6AMT1 , RPL14 , RPL36A
Biosynthesis of DHA-derived SPMs 0.0062563 0.6017211 0.4070179 0.8447307 1.760083 7 EPHX2, ALOX5, LTC4S
Lactose synthesis 0.0064048 0.6017211 0.4070179 -0.9852825 -1.389133 2 SLC2A1
Regulation of RUNX1 Expression and Activity 0.0066707 0.6017211 0.4070179 -0.7636883 -1.600099 18 MIR20A, MIR18A, MIR17 , AGO2
GTP hydrolysis and joining of the 60S ribosomal subunit 0.0068739 0.6017211 0.4070179 -0.5579842 -1.414787 94 EIF4E , RPS3A , RPL17 , RPS2 , RPS8 , EIF3M , RPL13 , RPL3 , RPL13A , RPS20 , RPS15 , EIF4G1 , RPLP1 , EIF3H , RPL9 , RPL18A , RPS11 , RPS7 , EIF3F , RPSA , RPS5 , EIF3J , RPL36 , RPS19 , RPS18 , RPS4X , RPS26 , RPL38 , RPL29 , RPS3 , EIF4A2 , RPL36AL, EIF4A1 , RPL28 , EIF4H , RPL12 , RPL7 
stat1 <- data.frame(stat1)
mres1 <- mitch_calc(stat1, genesets, priority="effect")
## Note: Enrichments with large effect sizes may not be
##             statistically significant.
head(mres1$enrichment_result,20) %>%
  kbl(caption="WG fry + mitch Reactome results") %>%
  kable_styling(full_width=FALSE)
WG fry + mitch Reactome results
set setSize pANOVA s.dist p.adjustANOVA
323 Digestion of dietary carbohydrate 10 0.0000389 -0.7511223 0.0016987
406 Expression and translocation of olfactory receptors 373 0.0000000 -0.6768069 0.0000000
869 Olfactory Signaling Pathway 381 0.0000000 -0.6674201 0.0000000
119 Beta defensins 33 0.0000000 -0.6487782 0.0000000
391 Endosomal/Vacuolar pathway 12 0.0001905 0.6219594 0.0053453
908 POU5F1 (OCT4), SOX2, NANOG repress genes related to differentiation 10 0.0007545 0.6151641 0.0160176
304 Defensins 41 0.0000000 -0.5980033 0.0000000
1465 Transcriptional regulation of pluripotent stem cells 31 0.0000000 0.5851783 0.0000016
749 Metallothioneins bind metals 11 0.0010229 0.5717804 0.0206030
55 Activation of the TFAP2 (AP-2) family of transcription factors 12 0.0006900 0.5656747 0.0150563
1136 Regulation of gene expression by Hypoxia-inducible Factor 11 0.0016642 0.5474586 0.0264082
380 ERKs are inactivated 13 0.0007187 0.5417071 0.0154662
1168 Response to metal ions 14 0.0005215 0.5354505 0.0120225
824 Negative regulation of activity of TFAP2 (AP-2) family transcription factors 10 0.0041448 0.5235066 0.0434101
86 Antimicrobial peptides 85 0.0000000 -0.5124541 0.0000000
1466 Transcriptional regulation of testis differentiation 13 0.0019574 0.4959543 0.0272815
121 Beta-catenin phosphorylation cascade 17 0.0004439 0.4919671 0.0108970
291 Defective GALNT3 causes HFTC 18 0.0003034 -0.4917030 0.0080798
907 POU5F1 (OCT4), SOX2, NANOG activate genes related to proliferation 13 0.0025011 0.4841983 0.0314333
1102 Regulation of FOXO transcriptional activity by acetylation 10 0.0085091 0.4804636 0.0726509 
stat2 <- data.frame(stat2)
mres2 <- mitch_calc(stat2, genesets, priority="effect")
## Note: Enrichments with large effect sizes may not be
##             statistically significant.
head(mres2$enrichment_result,20) %>%
  kbl(caption="Promoter fry + mitch Reactome results") %>%
  kable_styling(full_width=FALSE)
Promoter fry + mitch Reactome results
set setSize pANOVA s.dist p.adjustANOVA
293 Endosomal/Vacuolar pathway 11 0.0000691 0.6928876 0.0171727
963 Sema4D induced cell migration and growth-cone collapse 12 0.0016085 0.5259291 0.0663634
1195 Unwinding of DNA 11 0.0031961 -0.5134087 0.1168455
962 Sema4D in semaphorin signaling 15 0.0010268 0.4896528 0.0472695
189 Cytosolic iron-sulfur cluster assembly 10 0.0136978 0.4502339 0.2863544
196 DCC mediated attractive signaling 11 0.0175652 0.4135531 0.3411483
82 Basigin interactions 14 0.0074232 -0.4133221 0.2050444
935 SEMA3A-Plexin repulsion signaling by inhibiting Integrin adhesion 10 0.0253792 0.4083239 0.3801163
719 Phosphorylation of CD3 and TCR zeta chains 10 0.0291909 -0.3983384 0.3980716
961 Sema3A PAK dependent Axon repulsion 11 0.0224544 0.3975229 0.3736566
45 Amino acid transport across the plasma membrane 17 0.0049204 -0.3940336 0.1529014
551 Membrane binding and targetting of GAG proteins 12 0.0195514 0.3893259 0.3573888
1071 Synthesis And Processing Of GAG, GAGPOL Polyproteins 12 0.0195514 0.3893259 0.3573888
559 Metabolism of folate and pterines 11 0.0266478 -0.3860391 0.3807262
64 Assembly Of The HIV Virion 14 0.0124250 0.3859414 0.2757914
1213 WNT5A-dependent internalization of FZD4 10 0.0372170 0.3805291 0.4176170
858 Regulation of FZD by ubiquitination 12 0.0226050 0.3801898 0.3736566
1140 Trafficking and processing of endosomal TLR 10 0.0376292 0.3797064 0.4176170
723 Plasma lipoprotein remodeling 12 0.0245513 0.3749126 0.3801163
650 Nicotinamide salvaging 11 0.0316576 -0.3742108 0.4098998

save data object

save.image("GSE158422_fry.Rdata")