Gene set analysis
Overview
Teaching: XX min
Exercises: XX minQuestions
How do we find differentially expressed pathways?
Objectives
Explain how to find differentially expressed pathways with gene set analysis in R.
Understand how differentially expressed genes can enrich a gene set.
Explain how to perform a gene set analysis in R, using clusterProfiler.
Contribute!
This episode is intended to introduce the concept of how to carry out a functional analysis of a subset of differentially expressed (DE) genes, by means of assessing how significantly DE genes enrich gene sets of our interest.
First, we are going to explore the basic concept of enriching a gene set with differentially expressed (DE) genes. Recall the differential expression analysis.
library(SummarizedExperiment)
library(DESeq2)
se <- readRDS("data/GSE96870_se.rds")
dds <- DESeq2::DESeqDataSet(se[, se$tissue == "Cerebellum"],
design = ~ sex + time)
Warning in DESeq2::DESeqDataSet(se[, se$tissue == "Cerebellum"], design = ~sex + : some variables in design formula are
characters, converting to factors
dds <- DESeq2::DESeq(dds)
Fetch results for the contrast between male and female mice.
resSex <- DESeq2::results(dds, contrast = c("sex", "Male", "Female"))
summary(resSex)
out of 32652 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 53, 0.16%
LFC < 0 (down) : 71, 0.22%
outliers [1] : 10, 0.031%
low counts [2] : 13717, 42%
(mean count < 6)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results
Select DE genes between males and females with FDR < 5%.
sexDE <- as.data.frame(subset(resSex, padj < 0.05))
dim(sexDE)
[1] 54 6
sexDE <- sexDE[order(abs(sexDE$log2FoldChange), decreasing=TRUE), ]
head(sexDE)
baseMean log2FoldChange lfcSE stat pvalue padj
Eif2s3y 1410.8750 12.62514 0.5652155 22.33685 1.620659e-110 1.022366e-106
Kdm5d 692.1672 12.55386 0.5936267 21.14773 2.895664e-99 1.370011e-95
Uty 667.4375 12.01728 0.5935911 20.24505 3.927797e-91 1.486671e-87
Ddx3y 2072.9436 11.87241 0.3974927 29.86825 5.087220e-196 4.813782e-192
Xist 22603.0359 -11.60429 0.3362822 -34.50761 6.168523e-261 1.167393e-256
LOC105243748 52.9669 9.08325 0.5976242 15.19893 3.594320e-52 1.133708e-48
sexDEgenes <- rownames(sexDE)
head(sexDEgenes)
[1] "Eif2s3y" "Kdm5d" "Uty" "Ddx3y" "Xist" "LOC105243748"
length(sexDEgenes)
[1] 54
Enrichment of a curated gene set
Contribute!
Here we illustrate how to assess the enrichment of one gene set we curate ourselves with our subset of DE genes with sex-specific expression. Here we form such a gene set with genes from sex chromosomes. Could you think of another more accurate gene set formed by genes with sex-specific expression?
Build a gene set formed by genes located in the sex chromosomes X and Y.
xygenes <- rownames(se)[decode(seqnames(rowRanges(se)) %in% c("X", "Y"))]
length(xygenes)
[1] 2123
Build a contingency table and conduct a one-tailed Fisher’s exact test that verifies the association between genes being DE between male and female mice and being located in a sex chromosome.
N <- nrow(se)
n <- length(sexDEgenes)
m <- length(xygenes)
k <- length(intersect(xygenes, sexDEgenes))
dnames <- list(GS=c("inside", "outside"), DE=c("yes", "no"))
t <- matrix(c(k, n-k, m-k, N+k-n-m),
nrow=2, ncol=2, dimnames=dnames)
t
DE
GS yes no
inside 18 2105
outside 36 39627
fisher.test(t, alternative="greater")
Fisher's Exact Test for Count Data
data: t
p-value = 7.944e-11
alternative hypothesis: true odds ratio is greater than 1
95 percent confidence interval:
5.541517 Inf
sample estimates:
odds ratio
9.411737
Gene ontology analysis with clusterProfiler
Contribute!
Here we illustrate how to assess the enrichment on the entire collection of Gene Ontology (GO) gene sets using the package clusterProfiler. Could we illustrate any missing important feature of this package for this analysis objective? Could we briefly mention other packages that may be useful for this task?
Second, let’s perform a gene set analysis for an entire collection of gene sets using the Bioconductor package clusterProfiler. For this purpose, we will fetch the results for the contrast between two time points.
resTime <- DESeq2::results(dds, contrast = c("time", "Day8", "Day0"))
summary(resTime)
out of 32652 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 4472, 14%
LFC < 0 (down) : 4276, 13%
outliers [1] : 10, 0.031%
low counts [2] : 8732, 27%
(mean count < 1)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results
Select DE genes between Day0 and Day8 with FDR < 5% and minimum 1.5-fold
change.
timeDE <- as.data.frame(subset(resTime, padj < 0.05 & abs(log2FoldChange) > log2(1.5)))
dim(timeDE)
[1] 2110 6
timeDE <- timeDE[order(abs(timeDE$log2FoldChange), decreasing=TRUE), ]
head(timeDE)
baseMean log2FoldChange lfcSE stat pvalue padj
LOC105245444 2.441873 4.768938 0.9013067 5.291138 1.215573e-07 1.800765e-06
LOC105246405 9.728219 4.601505 0.6101832 7.541186 4.657174e-14 2.507951e-12
4933427D06Rik 1.480365 4.556126 1.0318402 4.415535 1.007607e-05 9.169093e-05
A930006I01Rik 2.312732 -4.353155 0.9176026 -4.744053 2.094837e-06 2.252139e-05
LOC105245223 3.272536 4.337202 0.8611255 5.036666 4.737099e-07 6.047199e-06
A530053G22Rik 1.554735 4.243903 1.0248977 4.140806 3.460875e-05 2.720142e-04
timeDEgenes <- rownames(timeDE)
head(timeDEgenes)
[1] "LOC105245444" "LOC105246405" "4933427D06Rik" "A930006I01Rik" "LOC105245223" "A530053G22Rik"
length(timeDEgenes)
[1] 2110
Call the enrichGO() function from
clusterProfiler
as follows.
library(clusterProfiler)
library(org.Mm.eg.db)
library(enrichplot)
resTimeGO <- enrichGO(gene = timeDEgenes,
keyType = "SYMBOL",
universe = rownames(se),
OrgDb = org.Mm.eg.db,
ont = "BP",
pvalueCutoff = 0.01,
qvalueCutoff = 0.01)
dim(resTimeGO)
[1] 32 9
head(resTimeGO)
ID Description GeneRatio BgRatio pvalue
GO:0071674 GO:0071674 mononuclear cell migration 32/1142 166/20469 6.296646e-10
GO:0035456 GO:0035456 response to interferon-beta 16/1142 48/20469 3.291098e-09
GO:0050900 GO:0050900 leukocyte migration 49/1142 355/20469 4.355926e-09
GO:0030595 GO:0030595 leukocyte chemotaxis 34/1142 214/20469 3.265849e-08
GO:0035458 GO:0035458 cellular response to interferon-beta 13/1142 38/20469 6.940867e-08
GO:0002523 GO:0002523 leukocyte migration involved in inflammatory response 10/1142 23/20469 1.649290e-07
p.adjust qvalue
GO:0071674 3.080319e-06 2.852712e-06
GO:0035456 7.103063e-06 6.578212e-06
GO:0050900 7.103063e-06 6.578212e-06
GO:0030595 3.994133e-05 3.699003e-05
GO:0035458 6.790944e-05 6.289156e-05
GO:0002523 1.344721e-04 1.245358e-04
geneID
GO:0071674 Tnfsf18/Aire/Ccl17/Ccr7/Nlrp12/Ccl2/Retnlg/Apod/Il12a/Ccl5/Fpr2/Fut7/Ccl7/Spn/Itgb3/Grem1/Ptk2b/Lgals3/Adam8/Dusp1/Ch25h/Nbl1/Alox5/Padi2/Plg/Calr/Ager/Ccl6/Mdk/Itga4/Hsd3b7/Trpm4
GO:0035456 Tgtp1/Tgtp2/F830016B08Rik/Iigp1/Ifitm6/Igtp/Gm4951/Bst2/Irgm1/Gbp6/Ifi47/Aim2/Ifitm7/Irgm2/Ifit1/Ifi204
GO:0050900 Tnfsf18/Aire/Ccl17/Ccr7/Nlrp12/Bst1/Ccl2/Retnlg/Ppbp/Cxcl5/Apod/Il12a/Ccl5/Fpr2/Umodl1/Fut7/Ccl7/Ccl28/Spn/Sell/Itgb3/Grem1/Cxcl1/Ptk2b/Lgals3/Adam8/Pf4/Dusp1/Ch25h/S100a8/Nbl1/Alox5/Padi2/Plg/Edn3/Il33/Ptn/Ada/Calr/Ager/Ccl6/Prex1/Aoc3/Itgam/Mdk/Itga4/Hsd3b7/P2ry12/Trpm4
GO:0030595 Tnfsf18/Ccl17/Ccr7/Bst1/Ccl2/Retnlg/Ppbp/Cxcl5/Il12a/Ccl5/Fpr2/Ccl7/Sell/Grem1/Cxcl1/Ptk2b/Lgals3/Adam8/Pf4/Dusp1/Ch25h/S100a8/Nbl1/Alox5/Padi2/Edn3/Ptn/Calr/Ccl6/Prex1/Itgam/Mdk/Hsd3b7/Trpm4
GO:0035458 Tgtp1/Tgtp2/F830016B08Rik/Iigp1/Igtp/Gm4951/Irgm1/Gbp6/Ifi47/Aim2/Irgm2/Ifit1/Ifi204
GO:0002523 Ccl2/Ppbp/Fut7/Adam8/S100a8/Alox5/Ptn/Aoc3/Itgam/Mdk
Count
GO:0071674 32
GO:0035456 16
GO:0050900 49
GO:0030595 34
GO:0035458 13
GO:0002523 10
Let’s build a more readable table of results.
library(kableExtra)
resTimeGOtab <- as.data.frame(resTimeGO)
resTimeGOtab$ID <- NULL
resTimeGOtab$geneID <- sapply(strsplit(resTimeGO$geneID, "/"), paste, collapse=", ")
ktab <- kable(resTimeGOtab, row.names=TRUE, caption="GO results for DE genes between time points.")
kable_styling(ktab, bootstrap_options=c("stripped", "hover", "responsive"), fixed_thead=TRUE)
| Description | GeneRatio | BgRatio | pvalue | p.adjust | qvalue | geneID | Count | |
|---|---|---|---|---|---|---|---|---|
| GO:0071674 | mononuclear cell migration | 32/1142 | 166/20469 | 0.00e+00 | 0.0000031 | 0.0000029 | Tnfsf18, Aire, Ccl17, Ccr7, Nlrp12, Ccl2, Retnlg, Apod, Il12a, Ccl5, Fpr2, Fut7, Ccl7, Spn, Itgb3, Grem1, Ptk2b, Lgals3, Adam8, Dusp1, Ch25h, Nbl1, Alox5, Padi2, Plg, Calr, Ager, Ccl6, Mdk, Itga4, Hsd3b7, Trpm4 | 32 |
| GO:0035456 | response to interferon-beta | 16/1142 | 48/20469 | 0.00e+00 | 0.0000071 | 0.0000066 | Tgtp1, Tgtp2, F830016B08Rik, Iigp1, Ifitm6, Igtp, Gm4951, Bst2, Irgm1, Gbp6, Ifi47, Aim2, Ifitm7, Irgm2, Ifit1, Ifi204 | 16 |
| GO:0050900 | leukocyte migration | 49/1142 | 355/20469 | 0.00e+00 | 0.0000071 | 0.0000066 | Tnfsf18, Aire, Ccl17, Ccr7, Nlrp12, Bst1, Ccl2, Retnlg, Ppbp, Cxcl5, Apod, Il12a, Ccl5, Fpr2, Umodl1, Fut7, Ccl7, Ccl28, Spn, Sell, Itgb3, Grem1, Cxcl1, Ptk2b, Lgals3, Adam8, Pf4, Dusp1, Ch25h, S100a8, Nbl1, Alox5, Padi2, Plg, Edn3, Il33, Ptn, Ada, Calr, Ager, Ccl6, Prex1, Aoc3, Itgam, Mdk, Itga4, Hsd3b7, P2ry12, Trpm4 | 49 |
| GO:0030595 | leukocyte chemotaxis | 34/1142 | 214/20469 | 0.00e+00 | 0.0000399 | 0.0000370 | Tnfsf18, Ccl17, Ccr7, Bst1, Ccl2, Retnlg, Ppbp, Cxcl5, Il12a, Ccl5, Fpr2, Ccl7, Sell, Grem1, Cxcl1, Ptk2b, Lgals3, Adam8, Pf4, Dusp1, Ch25h, S100a8, Nbl1, Alox5, Padi2, Edn3, Ptn, Calr, Ccl6, Prex1, Itgam, Mdk, Hsd3b7, Trpm4 | 34 |
| GO:0035458 | cellular response to interferon-beta | 13/1142 | 38/20469 | 1.00e-07 | 0.0000679 | 0.0000629 | Tgtp1, Tgtp2, F830016B08Rik, Iigp1, Igtp, Gm4951, Irgm1, Gbp6, Ifi47, Aim2, Irgm2, Ifit1, Ifi204 | 13 |
| GO:0002523 | leukocyte migration involved in inflammatory response | 10/1142 | 23/20469 | 2.00e-07 | 0.0001345 | 0.0001245 | Ccl2, Ppbp, Fut7, Adam8, S100a8, Alox5, Ptn, Aoc3, Itgam, Mdk | 10 |
| GO:0071675 | regulation of mononuclear cell migration | 21/1142 | 107/20469 | 4.00e-07 | 0.0002770 | 0.0002565 | Tnfsf18, Aire, Ccr7, Ccl2, Apod, Il12a, Ccl5, Fpr2, Spn, Itgb3, Grem1, Ptk2b, Lgals3, Adam8, Dusp1, Nbl1, Padi2, Calr, Ager, Mdk, Itga4 | 21 |
| GO:0002685 | regulation of leukocyte migration | 31/1142 | 213/20469 | 9.00e-07 | 0.0005212 | 0.0004827 | Tnfsf18, Aire, Ccr7, Bst1, Ccl2, Apod, Il12a, Ccl5, Fpr2, Fut7, Ccl28, Spn, Sell, Itgb3, Grem1, Ptk2b, Lgals3, Adam8, Dusp1, Nbl1, Padi2, Edn3, Il33, Ptn, Ada, Calr, Ager, Aoc3, Mdk, Itga4, P2ry12 | 31 |
| GO:0050953 | sensory perception of light stimulus | 26/1142 | 161/20469 | 1.00e-06 | 0.0005212 | 0.0004827 | Aipl1, Vsx2, Nxnl2, Lrit3, Cryba2, Bfsp2, Lrat, Gabrr2, Lum, Rlbp1, Pde6g, Gpr179, Col1a1, Cplx3, Best1, Ush1g, Rs1, Rdh5, Guca1b, Th, Ppef2, Rbp4, Olfm2, Rom1, Vsx1, Rpe65 | 26 |
| GO:0060326 | cell chemotaxis | 38/1142 | 298/20469 | 1.70e-06 | 0.0008479 | 0.0007853 | Tnfsf18, Ccl17, Ccr7, Bst1, Ccl2, Retnlg, Ppbp, Cxcl5, Nr4a1, Il12a, Ccl5, Fpr2, Ccl7, Ccl28, Sell, Grem1, Cxcl1, Ptk2b, Lgals3, Adam8, Pf4, Dusp1, Ch25h, S100a8, Nbl1, Alox5, Padi2, Edn3, Ptn, Plxnb3, Calr, Lpar1, Ccl6, Prex1, Itgam, Mdk, Hsd3b7, Trpm4 | 38 |
| GO:0007601 | visual perception | 25/1142 | 157/20469 | 2.00e-06 | 0.0008935 | 0.0008275 | Aipl1, Vsx2, Nxnl2, Lrit3, Cryba2, Bfsp2, Lrat, Gabrr2, Lum, Rlbp1, Pde6g, Gpr179, Col1a1, Cplx3, Best1, Rs1, Rdh5, Guca1b, Th, Ppef2, Rbp4, Olfm2, Rom1, Vsx1, Rpe65 | 25 |
| GO:0097529 | myeloid leukocyte migration | 30/1142 | 214/20469 | 3.10e-06 | 0.0012605 | 0.0011674 | Tnfsf18, Ccl17, Ccr7, Bst1, Ccl2, Retnlg, Ppbp, Cxcl5, Ccl5, Fpr2, Umodl1, Fut7, Ccl7, Sell, Grem1, Cxcl1, Ptk2b, Lgals3, Adam8, Pf4, Dusp1, S100a8, Nbl1, Edn3, Ager, Ccl6, Prex1, Itgam, Mdk, P2ry12 | 30 |
| GO:1990266 | neutrophil migration | 21/1142 | 122/20469 | 3.70e-06 | 0.0013884 | 0.0012858 | Ccl17, Ccr7, Bst1, Ccl2, Ppbp, Cxcl5, Ccl5, Umodl1, Fut7, Ccl7, Sell, Cxcl1, Lgals3, Adam8, Pf4, S100a8, Edn3, Ccl6, Prex1, Itgam, Mdk | 21 |
| GO:0030593 | neutrophil chemotaxis | 18/1142 | 98/20469 | 7.10e-06 | 0.0024639 | 0.0022819 | Ccl17, Ccr7, Bst1, Ccl2, Ppbp, Cxcl5, Ccl5, Ccl7, Sell, Cxcl1, Lgals3, Pf4, S100a8, Edn3, Ccl6, Prex1, Itgam, Mdk | 18 |
| GO:0071677 | positive regulation of mononuclear cell migration | 14/1142 | 64/20469 | 9.10e-06 | 0.0029614 | 0.0027426 | Tnfsf18, Ccr7, Ccl2, Il12a, Ccl5, Fpr2, Spn, Itgb3, Ptk2b, Lgals3, Adam8, Calr, Ager, Itga4 | 14 |
| GO:0030198 | extracellular matrix organization | 36/1142 | 297/20469 | 1.02e-05 | 0.0029937 | 0.0027725 | Nepn, Has2, Fbln5, Adamts14, Nox1, Adamtsl2, Mmp8, Lum, Itgb3, Nid1, Grem1, Elf3, Col5a3, Lgals3, Col1a1, Serpinh1, Col27a1, Loxl4, Agt, Kazald1, Colq, Pxdn, Plg, Col11a2, Col15a1, P4ha1, Mpzl3, Mmp15, Has3, Cav1, Ccdc80, Spint1, Abi3bp, Adamts16, Col14a1, Cyp1b1 | 36 |
| GO:0043062 | extracellular structure organization | 36/1142 | 298/20469 | 1.10e-05 | 0.0029937 | 0.0027725 | Nepn, Has2, Fbln5, Adamts14, Nox1, Adamtsl2, Mmp8, Lum, Itgb3, Nid1, Grem1, Elf3, Col5a3, Lgals3, Col1a1, Serpinh1, Col27a1, Loxl4, Agt, Kazald1, Colq, Pxdn, Plg, Col11a2, Col15a1, P4ha1, Mpzl3, Mmp15, Has3, Cav1, Ccdc80, Spint1, Abi3bp, Adamts16, Col14a1, Cyp1b1 | 36 |
| GO:0045229 | external encapsulating structure organization | 36/1142 | 298/20469 | 1.10e-05 | 0.0029937 | 0.0027725 | Nepn, Has2, Fbln5, Adamts14, Nox1, Adamtsl2, Mmp8, Lum, Itgb3, Nid1, Grem1, Elf3, Col5a3, Lgals3, Col1a1, Serpinh1, Col27a1, Loxl4, Agt, Kazald1, Colq, Pxdn, Plg, Col11a2, Col15a1, P4ha1, Mpzl3, Mmp15, Has3, Cav1, Ccdc80, Spint1, Abi3bp, Adamts16, Col14a1, Cyp1b1 | 36 |
| GO:0034341 | response to interferon-gamma | 21/1142 | 133/20469 | 1.48e-05 | 0.0038065 | 0.0035252 | Ccl17, Gbp4, Ccl2, Tgtp1, H2-Q7, Il12rb1, Ifitm6, Ccl5, Ccl7, Nos2, Nlrc5, Bst2, Irgm1, Gbp6, Capg, Ifitm7, Gbp9, Gbp5, Irgm2, Ccl6, Aqp4 | 21 |
| GO:0036336 | dendritic cell migration | 8/1142 | 23/20469 | 2.12e-05 | 0.0051736 | 0.0047913 | Tnfsf18, Ccr7, Nlrp12, Retnlg, Il12a, Alox5, Calr, Trpm4 | 8 |
| GO:0002819 | regulation of adaptive immune response | 27/1142 | 203/20469 | 2.49e-05 | 0.0058002 | 0.0053716 | Tnfsf18, Ccr7, H2-Q6, H2-Q7, Alox15, Il12a, Il12rb1, H2-Q4, Fut7, Spn, H2-Q2, Irf7, Cd274, Tnfrsf13c, Il33, H2-Q1, Ada, C3, Tfrc, H2-K1, Ager, H2-T23, Tap2, Tnfsf13b, Pla2g4a, Trpm4, Parp3 | 27 |
| GO:0001906 | cell killing | 26/1142 | 193/20469 | 2.79e-05 | 0.0060788 | 0.0056296 | Ccl17, Gzmb, Ccl2, Cxcl5, H2-Q6, H2-Q7, Il12a, H2-Q4, Il18rap, Ccl28, Nos2, Cxcl1, H2-Q2, Lgals3, Pf4, Tap1, H2-Q1, Emp2, Scnn1b, C3, H2-K1, Ager, H2-T23, Itgam, Tap2, Clec7a | 26 |
| GO:1903039 | positive regulation of leukocyte cell-cell adhesion | 28/1142 | 216/20469 | 2.86e-05 | 0.0060788 | 0.0056296 | Ccr7, Nr4a3, Has2, Ccl2, Il12a, Il12rb1, Ccl5, Fut7, Spn, Cd5, Icosl, Il2rg, Adam8, Cd274, Tnfrsf13c, Hsph1, Alox5, Btn2a2, Ada, Tfrc, Cd46, Ager, Xbp1, H2-T23, Tnfsf13b, Mdk, Itga4, Cav1 | 28 |
| GO:1901615 | organic hydroxy compound metabolic process | 50/1142 | 492/20469 | 3.17e-05 | 0.0064643 | 0.0059866 | Hao1, Dio3, Cyp1a1, Nr4a2, Sult1a1, Cyp4f18, Lrat, Ddc, Apoc1, Alox15, Lhcgr, Drd4, Cyp4f15, Acer2, Lcat, Hsd17b1, Ptk2b, Actn3, Akr1c14, Ch25h, Cyp11a1, Dct, Cyp2d22, Dkkl1, Cyp51, Srebf1, Scnn1b, Npc1l1, Moxd1, Msmo1, Hmgcs1, Ctsk, Ebp, Th, Qdpr, Abca1, Itgam, Kcnj6, Pla2g4a, Pmel, Cyb5r2, Cdh3, Rbp4, Hsd3b7, Idh2, Slc5a5, Tg, Rpe65, Gpr37, Cyp1b1 | 50 |
| GO:0097530 | granulocyte migration | 22/1142 | 151/20469 | 3.39e-05 | 0.0066403 | 0.0061496 | Tnfsf18, Ccl17, Ccr7, Bst1, Ccl2, Ppbp, Cxcl5, Ccl5, Umodl1, Fut7, Ccl7, Sell, Cxcl1, Lgals3, Adam8, Pf4, S100a8, Edn3, Ccl6, Prex1, Itgam, Mdk | 22 |
| GO:0007159 | leukocyte cell-cell adhesion | 38/1142 | 340/20469 | 3.71e-05 | 0.0069751 | 0.0064597 | Tnfsf18, Ccr7, Nr4a3, Has2, Slfn1, Ccl2, Il12a, Il12rb1, Ccl5, Fut7, Ccl28, Spn, Cd5, Sell, Icosl, Il2rg, Btn1a1, Lgals3, Adam8, Cd274, Tnfrsf13c, Hsph1, S100a8, Btla, Alox5, Btn2a2, Ada, Tfrc, Cd46, Ass1, Ager, Xbp1, H2-T23, Itgam, Tnfsf13b, Mdk, Itga4, Cav1 | 38 |
| GO:1903037 | regulation of leukocyte cell-cell adhesion | 35/1142 | 304/20469 | 4.03e-05 | 0.0072725 | 0.0067351 | Tnfsf18, Ccr7, Nr4a3, Has2, Slfn1, Ccl2, Il12a, Il12rb1, Ccl5, Fut7, Ccl28, Spn, Cd5, Icosl, Il2rg, Btn1a1, Lgals3, Adam8, Cd274, Tnfrsf13c, Hsph1, Btla, Alox5, Btn2a2, Ada, Tfrc, Cd46, Ass1, Ager, Xbp1, H2-T23, Tnfsf13b, Mdk, Itga4, Cav1 | 35 |
| GO:0031349 | positive regulation of defense response | 30/1142 | 244/20469 | 4.16e-05 | 0.0072725 | 0.0067351 | Tnfsf18, Ccr7, Zbp1, Pla2g3, Il12a, Ccl5, Mmp8, Fpr2, Il18rap, Nlrc5, Cxcl1, Adam8, Irf7, Irgm1, S100a8, Pla2g5, Aim2, Srebf1, Il33, C3, Npas2, Gbp5, Irgm2, Ager, Aoc3, H2-T23, Pla2g4a, Mdk, Ace, Ifi204 | 30 |
| GO:0002822 | regulation of adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains | 25/1142 | 187/20469 | 4.50e-05 | 0.0075878 | 0.0070271 | Tnfsf18, Ccr7, H2-Q6, H2-Q7, Il12a, Il12rb1, H2-Q4, Fut7, Spn, H2-Q2, Cd274, Tnfrsf13c, Il33, H2-Q1, Ada, C3, Tfrc, H2-K1, Ager, H2-T23, Tap2, Tnfsf13b, Pla2g4a, Trpm4, Parp3 | 25 |
| GO:0072676 | lymphocyte migration | 17/1142 | 102/20469 | 4.66e-05 | 0.0075967 | 0.0070354 | Aire, Ccl17, Ccr7, Ccl2, Apod, Ccl5, Fut7, Ccl7, Spn, Itgb3, Ptk2b, Adam8, Ch25h, Padi2, Ccl6, Itga4, Hsd3b7 | 17 |
| GO:0071621 | granulocyte chemotaxis | 19/1142 | 123/20469 | 5.07e-05 | 0.0079992 | 0.0074081 | Tnfsf18, Ccl17, Ccr7, Bst1, Ccl2, Ppbp, Cxcl5, Ccl5, Ccl7, Sell, Cxcl1, Lgals3, Pf4, S100a8, Edn3, Ccl6, Prex1, Itgam, Mdk | 19 |
| GO:0032103 | positive regulation of response to external stimulus | 41/1142 | 387/20469 | 6.37e-05 | 0.0097332 | 0.0090140 | Tnfsf18, Ccr7, Ccl2, Zbp1, Pla2g3, Ntf3, Il12a, Ccl5, Mmp8, Fpr2, Il18rap, Sell, Casr, Nlrc5, Cxcl1, Ptk2b, Adam8, Irf7, Irgm1, S100a8, Pla2g5, Aim2, Plg, Srebf1, Edn3, Il33, Ptn, C3, Calr, Lpar1, Gbp5, Irgm2, Ager, Aoc3, H2-T23, Pla2g4a, Mdk, Ace, Stx3, P2ry12, Ifi204 | 41 |
Key Points
Key point 1