EndPoints hormonal treatment - CTL04 WGCNA
Date: July 22, 2025
WGCNA on CTL04.
1. Environment Set Up
1.1 Values of RMarkdown parameters
knitr::opts_chunk$set(echo = TRUE, warning=FALSE)for (i in 1:length(params))
print(paste('Parameter:', names(params)[i], ' - Value:', params[[i]], '- Class:', class(params[[i]])))
## [1] "Parameter: Dataset - Value: CTL04 - Class: character"
## [1] "Parameter: OutputFolder - Value: ~/DataDir/bulkRNASeq/8.WGCNA/CTL04/3_ModuleFunctional/ - Class: character"library(dplyr)
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library(ggplot2)
library(viridis)
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library(SummarizedExperiment)
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## Loading required package: GenomicRanges
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library(AnnotationDbi)
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library(org.Hs.eg.db)
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library(topGO)
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OutputFolder <- params$OutputFolder
if (dir.exists(OutputFolder) == FALSE) {
dir.create(OutputFolder, recursive=TRUE)
}1.2 Helper functions
source('WGCNAHelper.R')2. Data Upload
2.1 Objects from first step
load('~/DataDir/bulkRNASeq/8.WGCNA/CTL04/2_ModuleCharacterization/GeneMetrics.RData')2.2 Modules of interest
modules <- c('turquoise', 'blue', 'green', 'brown',
'red', 'midnightblue', 'black', 'pink',
'magenta', 'purple', 'greenyellow', 'tan',
'cyan', 'grey60', 'lightgreen', 'lightyellow',
'royalblue', 'darkred')3. Gene Ontology Analysis: data preparation
3.1 Gene Vectors
GeneVectors <- topGOGeneVectors(GeneMetrics, modules)
names(GeneVectors)
## [1] "turquoise" "blue" "green" "brown" "red"
## [6] "midnightblue" "black" "pink" "magenta" "purple"
## [11] "greenyellow" "tan" "cyan" "grey60" "lightgreen"
## [16] "lightyellow" "royalblue" "darkred"3.2 Ontology Annotation
BPann <- topGO::annFUN.org(whichOnto="BP", feasibleGenes=names(GeneVectors[[1]]), mapping="org.Hs.eg.db", ID="symbol") %>% topGO::inverseList()
MFann <- topGO::annFUN.org(whichOnto="MF", feasibleGenes=names(GeneVectors[[1]]), mapping="org.Hs.eg.db", ID="symbol") %>% topGO::inverseList()
CCann <- topGO::annFUN.org(whichOnto="CC", feasibleGenes=names(GeneVectors[[1]]), mapping="org.Hs.eg.db", ID="symbol") %>% topGO::inverseList()4. Biological Processes
4.1 Enrichment
ResBP <- list()
for(i in 1:length(modules)){
Res <- topGOResults(Genes=GeneVectors[[modules[i]]], gene2GO=BPann, ontology='BP',
description=NULL, nodeSize=15, algorithm='weight01',
statistic='fisher', EnTh=2, PvalTh=0.01, minTerms=12)
print(paste('Significant BP terms for', modules[i], 'module:', dim(Res$ResSel)[1]))
ResBP[[i]] <- Res
names(ResBP)[i] <- modules[i]
write.table(Res$ResSel, file=paste0(OutputFolder, modules[i], '_BP.txt'), sep='\t', row.names=FALSE)
}
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## [1] "Significant BP terms for turquoise module: 120"
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## Annotating nodes ...............
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## [1] "Significant BP terms for blue module: 18"
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## Annotating nodes ...............
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## [1] "Significant BP terms for green module: 138"
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## Building most specific GOs .....
## ( 10083 GO terms found. )
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## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
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## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
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## -- Weight01 Algorithm --
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## the algorithm is scoring 3414 nontrivial nodes
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## [1] "Significant BP terms for brown module: 21"
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## Building most specific GOs .....
## ( 10083 GO terms found. )
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## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
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## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
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## -- Weight01 Algorithm --
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## the algorithm is scoring 3359 nontrivial nodes
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## [1] "Significant BP terms for red module: 51"
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## Building most specific GOs .....
## ( 10083 GO terms found. )
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## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
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## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
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## -- Weight01 Algorithm --
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## [1] "Significant BP terms for midnightblue module: 12"
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## Building most specific GOs .....
## ( 10083 GO terms found. )
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## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
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## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
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## -- Weight01 Algorithm --
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## the algorithm is scoring 3330 nontrivial nodes
## parameters:
## test statistic: fisher
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## [1] "Significant BP terms for black module: 51"
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## Building most specific GOs .....
## ( 10083 GO terms found. )
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## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
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## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
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## -- Weight01 Algorithm --
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## the algorithm is scoring 3213 nontrivial nodes
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## [1] "Significant BP terms for pink module: 12"
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## Building most specific GOs .....
## ( 10083 GO terms found. )
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## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
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## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
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## -- Weight01 Algorithm --
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## the algorithm is scoring 3206 nontrivial nodes
## parameters:
## test statistic: fisher
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## [1] "Significant BP terms for magenta module: 25"
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## Building most specific GOs .....
## ( 10083 GO terms found. )
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## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
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## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
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## -- Weight01 Algorithm --
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## the algorithm is scoring 2406 nontrivial nodes
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## test statistic: fisher
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## [1] "Significant BP terms for purple module: 12"
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## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
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## Annotating nodes ...............
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## -- Weight01 Algorithm --
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## the algorithm is scoring 2910 nontrivial nodes
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## test statistic: fisher
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## [1] "Significant BP terms for greenyellow module: 16"
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## Building most specific GOs .....
## ( 10083 GO terms found. )
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## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
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## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
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## -- Weight01 Algorithm --
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## the algorithm is scoring 3048 nontrivial nodes
## parameters:
## test statistic: fisher
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## [1] "Significant BP terms for tan module: 33"
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## Building most specific GOs .....
## ( 10083 GO terms found. )
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## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
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## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
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## -- Weight01 Algorithm --
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## the algorithm is scoring 2670 nontrivial nodes
## parameters:
## test statistic: fisher
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## Level 17: 1 nodes to be scored (0 eliminated genes)
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##
## Level 7: 440 nodes to be scored (5766 eliminated genes)
##
## Level 6: 429 nodes to be scored (6669 eliminated genes)
##
## Level 5: 292 nodes to be scored (7183 eliminated genes)
##
## Level 4: 169 nodes to be scored (7542 eliminated genes)
##
## Level 3: 77 nodes to be scored (7669 eliminated genes)
##
## Level 2: 16 nodes to be scored (7735 eliminated genes)
##
## Level 1: 1 nodes to be scored (7767 eliminated genes)
## [1] "Significant BP terms for cyan module: 14"
##
## Building most specific GOs .....
## ( 10083 GO terms found. )
##
## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
##
## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 2403 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 16: 1 nodes to be scored (0 eliminated genes)
##
## Level 15: 4 nodes to be scored (0 eliminated genes)
##
## Level 14: 10 nodes to be scored (33 eliminated genes)
##
## Level 13: 25 nodes to be scored (149 eliminated genes)
##
## Level 12: 48 nodes to be scored (487 eliminated genes)
##
## Level 11: 114 nodes to be scored (1595 eliminated genes)
##
## Level 10: 203 nodes to be scored (2593 eliminated genes)
##
## Level 9: 296 nodes to be scored (3325 eliminated genes)
##
## Level 8: 363 nodes to be scored (4151 eliminated genes)
##
## Level 7: 414 nodes to be scored (5288 eliminated genes)
##
## Level 6: 393 nodes to be scored (6355 eliminated genes)
##
## Level 5: 281 nodes to be scored (7103 eliminated genes)
##
## Level 4: 160 nodes to be scored (7499 eliminated genes)
##
## Level 3: 73 nodes to be scored (7666 eliminated genes)
##
## Level 2: 17 nodes to be scored (7733 eliminated genes)
##
## Level 1: 1 nodes to be scored (7768 eliminated genes)
## [1] "Significant BP terms for grey60 module: 49"
##
## Building most specific GOs .....
## ( 10083 GO terms found. )
##
## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
##
## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 2005 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 17: 1 nodes to be scored (0 eliminated genes)
##
## Level 16: 3 nodes to be scored (0 eliminated genes)
##
## Level 15: 7 nodes to be scored (20 eliminated genes)
##
## Level 14: 11 nodes to be scored (55 eliminated genes)
##
## Level 13: 20 nodes to be scored (160 eliminated genes)
##
## Level 12: 42 nodes to be scored (399 eliminated genes)
##
## Level 11: 88 nodes to be scored (1560 eliminated genes)
##
## Level 10: 146 nodes to be scored (2539 eliminated genes)
##
## Level 9: 224 nodes to be scored (3150 eliminated genes)
##
## Level 8: 269 nodes to be scored (4016 eliminated genes)
##
## Level 7: 344 nodes to be scored (5156 eliminated genes)
##
## Level 6: 360 nodes to be scored (6270 eliminated genes)
##
## Level 5: 255 nodes to be scored (7038 eliminated genes)
##
## Level 4: 150 nodes to be scored (7495 eliminated genes)
##
## Level 3: 67 nodes to be scored (7647 eliminated genes)
##
## Level 2: 17 nodes to be scored (7720 eliminated genes)
##
## Level 1: 1 nodes to be scored (7763 eliminated genes)
## [1] "Significant BP terms for lightgreen module: 47"
##
## Building most specific GOs .....
## ( 10083 GO terms found. )
##
## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
##
## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 1898 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 16: 1 nodes to be scored (0 eliminated genes)
##
## Level 15: 4 nodes to be scored (0 eliminated genes)
##
## Level 14: 12 nodes to be scored (15 eliminated genes)
##
## Level 13: 32 nodes to be scored (155 eliminated genes)
##
## Level 12: 46 nodes to be scored (439 eliminated genes)
##
## Level 11: 83 nodes to be scored (1668 eliminated genes)
##
## Level 10: 150 nodes to be scored (2536 eliminated genes)
##
## Level 9: 213 nodes to be scored (3133 eliminated genes)
##
## Level 8: 263 nodes to be scored (4010 eliminated genes)
##
## Level 7: 330 nodes to be scored (5128 eliminated genes)
##
## Level 6: 323 nodes to be scored (6146 eliminated genes)
##
## Level 5: 238 nodes to be scored (6953 eliminated genes)
##
## Level 4: 124 nodes to be scored (7456 eliminated genes)
##
## Level 3: 63 nodes to be scored (7653 eliminated genes)
##
## Level 2: 15 nodes to be scored (7720 eliminated genes)
##
## Level 1: 1 nodes to be scored (7767 eliminated genes)
## [1] "Significant BP terms for lightyellow module: 21"
##
## Building most specific GOs .....
## ( 10083 GO terms found. )
##
## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
##
## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 1444 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 15: 1 nodes to be scored (0 eliminated genes)
##
## Level 14: 5 nodes to be scored (0 eliminated genes)
##
## Level 13: 14 nodes to be scored (50 eliminated genes)
##
## Level 12: 25 nodes to be scored (254 eliminated genes)
##
## Level 11: 45 nodes to be scored (1404 eliminated genes)
##
## Level 10: 88 nodes to be scored (2258 eliminated genes)
##
## Level 9: 142 nodes to be scored (2799 eliminated genes)
##
## Level 8: 203 nodes to be scored (3537 eliminated genes)
##
## Level 7: 239 nodes to be scored (5014 eliminated genes)
##
## Level 6: 257 nodes to be scored (6166 eliminated genes)
##
## Level 5: 219 nodes to be scored (6886 eliminated genes)
##
## Level 4: 122 nodes to be scored (7438 eliminated genes)
##
## Level 3: 66 nodes to be scored (7636 eliminated genes)
##
## Level 2: 17 nodes to be scored (7708 eliminated genes)
##
## Level 1: 1 nodes to be scored (7762 eliminated genes)
## [1] "Significant BP terms for royalblue module: 12"
##
## Building most specific GOs .....
## ( 10083 GO terms found. )
##
## Build GO DAG topology ..........
## ( 13757 GO terms and 31099 relations. )
##
## Annotating nodes ...............
## ( 7845 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 1338 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 16: 2 nodes to be scored (0 eliminated genes)
##
## Level 15: 3 nodes to be scored (0 eliminated genes)
##
## Level 14: 8 nodes to be scored (48 eliminated genes)
##
## Level 13: 17 nodes to be scored (90 eliminated genes)
##
## Level 12: 29 nodes to be scored (331 eliminated genes)
##
## Level 11: 47 nodes to be scored (1429 eliminated genes)
##
## Level 10: 82 nodes to be scored (2337 eliminated genes)
##
## Level 9: 144 nodes to be scored (2893 eliminated genes)
##
## Level 8: 155 nodes to be scored (3603 eliminated genes)
##
## Level 7: 228 nodes to be scored (4708 eliminated genes)
##
## Level 6: 238 nodes to be scored (5859 eliminated genes)
##
## Level 5: 198 nodes to be scored (6791 eliminated genes)
##
## Level 4: 112 nodes to be scored (7372 eliminated genes)
##
## Level 3: 59 nodes to be scored (7645 eliminated genes)
##
## Level 2: 15 nodes to be scored (7720 eliminated genes)
##
## Level 1: 1 nodes to be scored (7767 eliminated genes)
## [1] "Significant BP terms for darkred module: 12"4.2 Barplots
GOPlots <- list()
for(i in 1:length(modules)){
Plot <- topGOBarplot(ResBP[[i]]$ResSel, terms=12, pvalTh=0.01, title=modules[i], palette=NULL)
GOPlots$BP_Bar[[i]] <- Plot
names(GOPlots$BP_Bar)[i] <- modules[i]
}BPBar <- gridExtra::grid.arrange(GOPlots$BP_Bar$turquoise, GOPlots$BP_Bar$blue, GOPlots$BP_Bar$green, GOPlots$BP_Bar$brown,
GOPlots$BP_Bar$red, GOPlots$BP_Bar$midnightblue, GOPlots$BP_Bar$black, GOPlots$BP_Bar$pink,
GOPlots$BP_Bar$magenta, GOPlots$BP_Bar$purple, GOPlots$BP_Bar$greenyellow, GOPlots$BP_Bar$tan,
GOPlots$BP_Bar$cyan, GOPlots$BP_Bar$grey60, GOPlots$BP_Bar$lightgreen, GOPlots$BP_Bar$lightyellow,
GOPlots$BP_Bar$royalblue, GOPlots$BP_Bar$darkred,
ncol=4)
ggsave(file=paste0(OutputFolder, 'BP_Barplot.pdf'), BPBar, width=25, height=25)
BPBar## TableGrob (5 x 4) "arrange": 18 grobs
## z cells name grob
## 1 1 (1-1,1-1) arrange gtable[layout]
## 2 2 (1-1,2-2) arrange gtable[layout]
## 3 3 (1-1,3-3) arrange gtable[layout]
## 4 4 (1-1,4-4) arrange gtable[layout]
## 5 5 (2-2,1-1) arrange gtable[layout]
## 6 6 (2-2,2-2) arrange gtable[layout]
## 7 7 (2-2,3-3) arrange gtable[layout]
## 8 8 (2-2,4-4) arrange gtable[layout]
## 9 9 (3-3,1-1) arrange gtable[layout]
## 10 10 (3-3,2-2) arrange gtable[layout]
## 11 11 (3-3,3-3) arrange gtable[layout]
## 12 12 (3-3,4-4) arrange gtable[layout]
## 13 13 (4-4,1-1) arrange gtable[layout]
## 14 14 (4-4,2-2) arrange gtable[layout]
## 15 15 (4-4,3-3) arrange gtable[layout]
## 16 16 (4-4,4-4) arrange gtable[layout]
## 17 17 (5-5,1-1) arrange gtable[layout]
## 18 18 (5-5,2-2) arrange gtable[layout]5. Molecular Function
5.1 Enrichment
ResMF <- list()
for(i in 1:length(modules)){
Res <- topGOResults(Genes=GeneVectors[[modules[i]]], gene2GO=MFann, ontology='MF',
description=NULL, nodeSize=15, algorithm='weight01',
statistic='fisher', EnTh=2, PvalTh=0.01, minTerms=12)
print(paste('Significant MF terms for', modules[i], 'module:', dim(Res$ResSel)[1]))
ResMF[[i]] <- Res
names(ResMF)[i] <- modules[i]
write.table(Res$ResSel, file=paste0(OutputFolder, modules[i], '_MF.txt'), sep='\t', row.names=FALSE)
}
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 600 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 6 nodes to be scored (0 eliminated genes)
##
## Level 10: 8 nodes to be scored (0 eliminated genes)
##
## Level 9: 22 nodes to be scored (129 eliminated genes)
##
## Level 8: 33 nodes to be scored (841 eliminated genes)
##
## Level 7: 68 nodes to be scored (1985 eliminated genes)
##
## Level 6: 111 nodes to be scored (2303 eliminated genes)
##
## Level 5: 143 nodes to be scored (3177 eliminated genes)
##
## Level 4: 145 nodes to be scored (5073 eliminated genes)
##
## Level 3: 48 nodes to be scored (6445 eliminated genes)
##
## Level 2: 15 nodes to be scored (7003 eliminated genes)
##
## Level 1: 1 nodes to be scored (7960 eliminated genes)
## [1] "Significant MF terms for turquoise module: 33"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 557 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 4 nodes to be scored (0 eliminated genes)
##
## Level 10: 7 nodes to be scored (0 eliminated genes)
##
## Level 9: 21 nodes to be scored (98 eliminated genes)
##
## Level 8: 27 nodes to be scored (831 eliminated genes)
##
## Level 7: 61 nodes to be scored (1989 eliminated genes)
##
## Level 6: 101 nodes to be scored (2268 eliminated genes)
##
## Level 5: 133 nodes to be scored (3116 eliminated genes)
##
## Level 4: 137 nodes to be scored (4989 eliminated genes)
##
## Level 3: 49 nodes to be scored (6404 eliminated genes)
##
## Level 2: 16 nodes to be scored (6983 eliminated genes)
##
## Level 1: 1 nodes to be scored (7960 eliminated genes)
## [1] "Significant MF terms for blue module: 16"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 512 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 2 nodes to be scored (0 eliminated genes)
##
## Level 10: 4 nodes to be scored (0 eliminated genes)
##
## Level 9: 15 nodes to be scored (71 eliminated genes)
##
## Level 8: 28 nodes to be scored (732 eliminated genes)
##
## Level 7: 62 nodes to be scored (1948 eliminated genes)
##
## Level 6: 95 nodes to be scored (2290 eliminated genes)
##
## Level 5: 116 nodes to be scored (3121 eliminated genes)
##
## Level 4: 127 nodes to be scored (4844 eliminated genes)
##
## Level 3: 47 nodes to be scored (6314 eliminated genes)
##
## Level 2: 15 nodes to be scored (6945 eliminated genes)
##
## Level 1: 1 nodes to be scored (7960 eliminated genes)
## [1] "Significant MF terms for green module: 25"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 545 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 2 nodes to be scored (0 eliminated genes)
##
## Level 10: 8 nodes to be scored (0 eliminated genes)
##
## Level 9: 18 nodes to be scored (62 eliminated genes)
##
## Level 8: 30 nodes to be scored (841 eliminated genes)
##
## Level 7: 62 nodes to be scored (1975 eliminated genes)
##
## Level 6: 95 nodes to be scored (2288 eliminated genes)
##
## Level 5: 127 nodes to be scored (3098 eliminated genes)
##
## Level 4: 139 nodes to be scored (4963 eliminated genes)
##
## Level 3: 48 nodes to be scored (6409 eliminated genes)
##
## Level 2: 15 nodes to be scored (6995 eliminated genes)
##
## Level 1: 1 nodes to be scored (7960 eliminated genes)
## [1] "Significant MF terms for brown module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 505 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 2 nodes to be scored (0 eliminated genes)
##
## Level 10: 4 nodes to be scored (0 eliminated genes)
##
## Level 9: 14 nodes to be scored (71 eliminated genes)
##
## Level 8: 24 nodes to be scored (723 eliminated genes)
##
## Level 7: 62 nodes to be scored (1918 eliminated genes)
##
## Level 6: 96 nodes to be scored (2252 eliminated genes)
##
## Level 5: 118 nodes to be scored (3123 eliminated genes)
##
## Level 4: 121 nodes to be scored (4959 eliminated genes)
##
## Level 3: 48 nodes to be scored (6361 eliminated genes)
##
## Level 2: 15 nodes to be scored (6948 eliminated genes)
##
## Level 1: 1 nodes to be scored (7957 eliminated genes)
## [1] "Significant MF terms for red module: 19"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 468 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 5 nodes to be scored (0 eliminated genes)
##
## Level 10: 5 nodes to be scored (0 eliminated genes)
##
## Level 9: 19 nodes to be scored (99 eliminated genes)
##
## Level 8: 29 nodes to be scored (801 eliminated genes)
##
## Level 7: 53 nodes to be scored (1981 eliminated genes)
##
## Level 6: 77 nodes to be scored (2251 eliminated genes)
##
## Level 5: 115 nodes to be scored (2977 eliminated genes)
##
## Level 4: 108 nodes to be scored (4710 eliminated genes)
##
## Level 3: 42 nodes to be scored (6279 eliminated genes)
##
## Level 2: 14 nodes to be scored (6910 eliminated genes)
##
## Level 1: 1 nodes to be scored (7954 eliminated genes)
## [1] "Significant MF terms for midnightblue module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 491 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 1 nodes to be scored (0 eliminated genes)
##
## Level 10: 1 nodes to be scored (0 eliminated genes)
##
## Level 9: 16 nodes to be scored (30 eliminated genes)
##
## Level 8: 26 nodes to be scored (653 eliminated genes)
##
## Level 7: 54 nodes to be scored (1896 eliminated genes)
##
## Level 6: 87 nodes to be scored (2252 eliminated genes)
##
## Level 5: 117 nodes to be scored (3043 eliminated genes)
##
## Level 4: 127 nodes to be scored (4867 eliminated genes)
##
## Level 3: 45 nodes to be scored (6364 eliminated genes)
##
## Level 2: 16 nodes to be scored (6971 eliminated genes)
##
## Level 1: 1 nodes to be scored (7957 eliminated genes)
## [1] "Significant MF terms for black module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 479 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 1 nodes to be scored (0 eliminated genes)
##
## Level 10: 3 nodes to be scored (0 eliminated genes)
##
## Level 9: 14 nodes to be scored (21 eliminated genes)
##
## Level 8: 26 nodes to be scored (742 eliminated genes)
##
## Level 7: 54 nodes to be scored (1889 eliminated genes)
##
## Level 6: 84 nodes to be scored (2282 eliminated genes)
##
## Level 5: 113 nodes to be scored (3081 eliminated genes)
##
## Level 4: 123 nodes to be scored (4858 eliminated genes)
##
## Level 3: 45 nodes to be scored (6345 eliminated genes)
##
## Level 2: 15 nodes to be scored (6945 eliminated genes)
##
## Level 1: 1 nodes to be scored (7960 eliminated genes)
## [1] "Significant MF terms for pink module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 470 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 4 nodes to be scored (0 eliminated genes)
##
## Level 10: 6 nodes to be scored (0 eliminated genes)
##
## Level 9: 16 nodes to be scored (103 eliminated genes)
##
## Level 8: 26 nodes to be scored (806 eliminated genes)
##
## Level 7: 47 nodes to be scored (1917 eliminated genes)
##
## Level 6: 82 nodes to be scored (2244 eliminated genes)
##
## Level 5: 110 nodes to be scored (2934 eliminated genes)
##
## Level 4: 121 nodes to be scored (4832 eliminated genes)
##
## Level 3: 43 nodes to be scored (6335 eliminated genes)
##
## Level 2: 14 nodes to be scored (6959 eliminated genes)
##
## Level 1: 1 nodes to be scored (7957 eliminated genes)
## [1] "Significant MF terms for magenta module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 341 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 1 nodes to be scored (0 eliminated genes)
##
## Level 10: 3 nodes to be scored (0 eliminated genes)
##
## Level 9: 14 nodes to be scored (41 eliminated genes)
##
## Level 8: 20 nodes to be scored (705 eliminated genes)
##
## Level 7: 40 nodes to be scored (1870 eliminated genes)
##
## Level 6: 68 nodes to be scored (2172 eliminated genes)
##
## Level 5: 73 nodes to be scored (2872 eliminated genes)
##
## Level 4: 76 nodes to be scored (4441 eliminated genes)
##
## Level 3: 33 nodes to be scored (5947 eliminated genes)
##
## Level 2: 12 nodes to be scored (6769 eliminated genes)
##
## Level 1: 1 nodes to be scored (7947 eliminated genes)
## [1] "Significant MF terms for purple module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 432 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 6 nodes to be scored (0 eliminated genes)
##
## Level 10: 6 nodes to be scored (0 eliminated genes)
##
## Level 9: 17 nodes to be scored (129 eliminated genes)
##
## Level 8: 25 nodes to be scored (819 eliminated genes)
##
## Level 7: 43 nodes to be scored (1958 eliminated genes)
##
## Level 6: 71 nodes to be scored (2234 eliminated genes)
##
## Level 5: 112 nodes to be scored (2914 eliminated genes)
##
## Level 4: 100 nodes to be scored (4760 eliminated genes)
##
## Level 3: 40 nodes to be scored (6322 eliminated genes)
##
## Level 2: 11 nodes to be scored (6884 eliminated genes)
##
## Level 1: 1 nodes to be scored (7954 eliminated genes)
## [1] "Significant MF terms for greenyellow module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 472 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 4 nodes to be scored (0 eliminated genes)
##
## Level 10: 8 nodes to be scored (0 eliminated genes)
##
## Level 9: 15 nodes to be scored (98 eliminated genes)
##
## Level 8: 22 nodes to be scored (841 eliminated genes)
##
## Level 7: 47 nodes to be scored (1904 eliminated genes)
##
## Level 6: 77 nodes to be scored (2199 eliminated genes)
##
## Level 5: 115 nodes to be scored (2969 eliminated genes)
##
## Level 4: 129 nodes to be scored (4813 eliminated genes)
##
## Level 3: 42 nodes to be scored (6331 eliminated genes)
##
## Level 2: 12 nodes to be scored (6960 eliminated genes)
##
## Level 1: 1 nodes to be scored (7954 eliminated genes)
## [1] "Significant MF terms for tan module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 416 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 3 nodes to be scored (0 eliminated genes)
##
## Level 10: 5 nodes to be scored (0 eliminated genes)
##
## Level 9: 12 nodes to be scored (78 eliminated genes)
##
## Level 8: 21 nodes to be scored (788 eliminated genes)
##
## Level 7: 43 nodes to be scored (1918 eliminated genes)
##
## Level 6: 77 nodes to be scored (2205 eliminated genes)
##
## Level 5: 98 nodes to be scored (2902 eliminated genes)
##
## Level 4: 106 nodes to be scored (4807 eliminated genes)
##
## Level 3: 36 nodes to be scored (6259 eliminated genes)
##
## Level 2: 14 nodes to be scored (6862 eliminated genes)
##
## Level 1: 1 nodes to be scored (7940 eliminated genes)
## [1] "Significant MF terms for cyan module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 296 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 2 nodes to be scored (0 eliminated genes)
##
## Level 10: 3 nodes to be scored (0 eliminated genes)
##
## Level 9: 9 nodes to be scored (40 eliminated genes)
##
## Level 8: 14 nodes to be scored (740 eliminated genes)
##
## Level 7: 29 nodes to be scored (1714 eliminated genes)
##
## Level 6: 49 nodes to be scored (1954 eliminated genes)
##
## Level 5: 71 nodes to be scored (2739 eliminated genes)
##
## Level 4: 72 nodes to be scored (4332 eliminated genes)
##
## Level 3: 34 nodes to be scored (5950 eliminated genes)
##
## Level 2: 12 nodes to be scored (6662 eliminated genes)
##
## Level 1: 1 nodes to be scored (7953 eliminated genes)
## [1] "Significant MF terms for grey60 module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 297 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 3 nodes to be scored (0 eliminated genes)
##
## Level 10: 4 nodes to be scored (0 eliminated genes)
##
## Level 9: 14 nodes to be scored (92 eliminated genes)
##
## Level 8: 19 nodes to be scored (774 eliminated genes)
##
## Level 7: 32 nodes to be scored (1932 eliminated genes)
##
## Level 6: 58 nodes to be scored (2202 eliminated genes)
##
## Level 5: 67 nodes to be scored (2832 eliminated genes)
##
## Level 4: 65 nodes to be scored (4373 eliminated genes)
##
## Level 3: 27 nodes to be scored (5970 eliminated genes)
##
## Level 2: 7 nodes to be scored (6673 eliminated genes)
##
## Level 1: 1 nodes to be scored (7925 eliminated genes)
## [1] "Significant MF terms for lightgreen module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 261 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 1 nodes to be scored (0 eliminated genes)
##
## Level 10: 2 nodes to be scored (0 eliminated genes)
##
## Level 9: 7 nodes to be scored (30 eliminated genes)
##
## Level 8: 7 nodes to be scored (689 eliminated genes)
##
## Level 7: 26 nodes to be scored (1764 eliminated genes)
##
## Level 6: 44 nodes to be scored (1913 eliminated genes)
##
## Level 5: 64 nodes to be scored (2610 eliminated genes)
##
## Level 4: 69 nodes to be scored (4299 eliminated genes)
##
## Level 3: 30 nodes to be scored (5965 eliminated genes)
##
## Level 2: 10 nodes to be scored (6639 eliminated genes)
##
## Level 1: 1 nodes to be scored (7914 eliminated genes)
## [1] "Significant MF terms for lightyellow module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 238 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 1 nodes to be scored (0 eliminated genes)
##
## Level 10: 2 nodes to be scored (0 eliminated genes)
##
## Level 9: 7 nodes to be scored (30 eliminated genes)
##
## Level 8: 8 nodes to be scored (671 eliminated genes)
##
## Level 7: 22 nodes to be scored (1773 eliminated genes)
##
## Level 6: 40 nodes to be scored (1892 eliminated genes)
##
## Level 5: 59 nodes to be scored (2506 eliminated genes)
##
## Level 4: 61 nodes to be scored (3928 eliminated genes)
##
## Level 3: 25 nodes to be scored (5772 eliminated genes)
##
## Level 2: 12 nodes to be scored (6674 eliminated genes)
##
## Level 1: 1 nodes to be scored (7917 eliminated genes)
## [1] "Significant MF terms for royalblue module: 12"
##
## Building most specific GOs .....
## ( 3392 GO terms found. )
##
## Build GO DAG topology ..........
## ( 3881 GO terms and 5078 relations. )
##
## Annotating nodes ...............
## ( 8039 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 195 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 10: 1 nodes to be scored (0 eliminated genes)
##
## Level 9: 5 nodes to be scored (0 eliminated genes)
##
## Level 8: 8 nodes to be scored (653 eliminated genes)
##
## Level 7: 19 nodes to be scored (1714 eliminated genes)
##
## Level 6: 31 nodes to be scored (1833 eliminated genes)
##
## Level 5: 45 nodes to be scored (2341 eliminated genes)
##
## Level 4: 54 nodes to be scored (3377 eliminated genes)
##
## Level 3: 23 nodes to be scored (5425 eliminated genes)
##
## Level 2: 8 nodes to be scored (6446 eliminated genes)
##
## Level 1: 1 nodes to be scored (7891 eliminated genes)
## [1] "Significant MF terms for darkred module: 12"5.2 Barplots
for(i in 1:length(modules)){
Plot <- topGOBarplot(ResMF[[i]]$ResSel, terms=12, pvalTh=0.01, title=modules[i], palette=NULL)
GOPlots$MF_Bar[[i]] <- Plot
names(GOPlots$MF_Bar)[i] <- modules[i]
}MFBar <- gridExtra::grid.arrange(GOPlots$MF_Bar$turquoise, GOPlots$MF_Bar$blue, GOPlots$MF_Bar$green, GOPlots$MF_Bar$brown,
GOPlots$MF_Bar$red, GOPlots$MF_Bar$midnightblue, GOPlots$MF_Bar$black, GOPlots$MF_Bar$pink,
GOPlots$MF_Bar$magenta, GOPlots$MF_Bar$purple, GOPlots$MF_Bar$greenyellow, GOPlots$MF_Bar$tan,
GOPlots$MF_Bar$cyan, GOPlots$MF_Bar$grey60, GOPlots$MF_Bar$lightgreen, GOPlots$MF_Bar$lightyellow,
GOPlots$MF_Bar$royalblue, GOPlots$MF_Bar$darkred,
ncol=4)
ggsave(file=paste0(OutputFolder, 'MFBarplot.pdf'), MFBar, width=25, height=25)
MFBar## TableGrob (5 x 4) "arrange": 18 grobs
## z cells name grob
## 1 1 (1-1,1-1) arrange gtable[layout]
## 2 2 (1-1,2-2) arrange gtable[layout]
## 3 3 (1-1,3-3) arrange gtable[layout]
## 4 4 (1-1,4-4) arrange gtable[layout]
## 5 5 (2-2,1-1) arrange gtable[layout]
## 6 6 (2-2,2-2) arrange gtable[layout]
## 7 7 (2-2,3-3) arrange gtable[layout]
## 8 8 (2-2,4-4) arrange gtable[layout]
## 9 9 (3-3,1-1) arrange gtable[layout]
## 10 10 (3-3,2-2) arrange gtable[layout]
## 11 11 (3-3,3-3) arrange gtable[layout]
## 12 12 (3-3,4-4) arrange gtable[layout]
## 13 13 (4-4,1-1) arrange gtable[layout]
## 14 14 (4-4,2-2) arrange gtable[layout]
## 15 15 (4-4,3-3) arrange gtable[layout]
## 16 16 (4-4,4-4) arrange gtable[layout]
## 17 17 (5-5,1-1) arrange gtable[layout]
## 18 18 (5-5,2-2) arrange gtable[layout]6. Cellular Component
6.1 Enrichment
ResCC <- list()
for(i in 1:length(modules)){
Res <- topGOResults(Genes=GeneVectors[[modules[i]]], gene2GO=CCann, ontology='CC',
description=NULL, nodeSize=15, algorithm='weight01',
statistic='fisher', EnTh=2, PvalTh=0.01, minTerms=12)
print(paste('Significant CC terms for', modules[i], 'module:', dim(Res$ResSel)[1]))
ResCC[[i]] <- Res
names(ResCC)[i] <- modules[i]
write.table(Res$ResSel, file=paste0(OutputFolder, modules[i], '_CC-.txt'), sep='\t', row.names=FALSE)
}
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 478 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 13: 1 nodes to be scored (0 eliminated genes)
##
## Level 12: 1 nodes to be scored (0 eliminated genes)
##
## Level 11: 15 nodes to be scored (24 eliminated genes)
##
## Level 10: 43 nodes to be scored (32 eliminated genes)
##
## Level 9: 67 nodes to be scored (406 eliminated genes)
##
## Level 8: 73 nodes to be scored (1414 eliminated genes)
##
## Level 7: 73 nodes to be scored (2728 eliminated genes)
##
## Level 6: 69 nodes to be scored (4756 eliminated genes)
##
## Level 5: 59 nodes to be scored (5885 eliminated genes)
##
## Level 4: 40 nodes to be scored (7113 eliminated genes)
##
## Level 3: 34 nodes to be scored (7865 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for turquoise module: 45"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 467 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 13: 1 nodes to be scored (0 eliminated genes)
##
## Level 12: 1 nodes to be scored (0 eliminated genes)
##
## Level 11: 14 nodes to be scored (24 eliminated genes)
##
## Level 10: 42 nodes to be scored (32 eliminated genes)
##
## Level 9: 67 nodes to be scored (389 eliminated genes)
##
## Level 8: 72 nodes to be scored (1404 eliminated genes)
##
## Level 7: 74 nodes to be scored (2775 eliminated genes)
##
## Level 6: 66 nodes to be scored (4736 eliminated genes)
##
## Level 5: 56 nodes to be scored (5880 eliminated genes)
##
## Level 4: 37 nodes to be scored (7112 eliminated genes)
##
## Level 3: 34 nodes to be scored (7865 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for blue module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 426 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 12 nodes to be scored (0 eliminated genes)
##
## Level 10: 31 nodes to be scored (0 eliminated genes)
##
## Level 9: 60 nodes to be scored (273 eliminated genes)
##
## Level 8: 68 nodes to be scored (1166 eliminated genes)
##
## Level 7: 68 nodes to be scored (2592 eliminated genes)
##
## Level 6: 62 nodes to be scored (4706 eliminated genes)
##
## Level 5: 53 nodes to be scored (5872 eliminated genes)
##
## Level 4: 34 nodes to be scored (7108 eliminated genes)
##
## Level 3: 35 nodes to be scored (7864 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for green module: 44"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 447 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 13: 1 nodes to be scored (0 eliminated genes)
##
## Level 12: 1 nodes to be scored (0 eliminated genes)
##
## Level 11: 14 nodes to be scored (24 eliminated genes)
##
## Level 10: 40 nodes to be scored (32 eliminated genes)
##
## Level 9: 62 nodes to be scored (389 eliminated genes)
##
## Level 8: 65 nodes to be scored (1402 eliminated genes)
##
## Level 7: 73 nodes to be scored (2720 eliminated genes)
##
## Level 6: 62 nodes to be scored (4707 eliminated genes)
##
## Level 5: 55 nodes to be scored (5884 eliminated genes)
##
## Level 4: 36 nodes to be scored (7106 eliminated genes)
##
## Level 3: 35 nodes to be scored (7865 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for brown module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 430 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 10 nodes to be scored (0 eliminated genes)
##
## Level 10: 33 nodes to be scored (0 eliminated genes)
##
## Level 9: 61 nodes to be scored (295 eliminated genes)
##
## Level 8: 65 nodes to be scored (1261 eliminated genes)
##
## Level 7: 70 nodes to be scored (2694 eliminated genes)
##
## Level 6: 62 nodes to be scored (4714 eliminated genes)
##
## Level 5: 55 nodes to be scored (5876 eliminated genes)
##
## Level 4: 38 nodes to be scored (7109 eliminated genes)
##
## Level 3: 33 nodes to be scored (7863 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for red module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 408 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 13: 1 nodes to be scored (0 eliminated genes)
##
## Level 12: 1 nodes to be scored (0 eliminated genes)
##
## Level 11: 9 nodes to be scored (24 eliminated genes)
##
## Level 10: 33 nodes to be scored (32 eliminated genes)
##
## Level 9: 58 nodes to be scored (264 eliminated genes)
##
## Level 8: 62 nodes to be scored (1285 eliminated genes)
##
## Level 7: 55 nodes to be scored (2662 eliminated genes)
##
## Level 6: 65 nodes to be scored (4660 eliminated genes)
##
## Level 5: 56 nodes to be scored (5820 eliminated genes)
##
## Level 4: 32 nodes to be scored (7098 eliminated genes)
##
## Level 3: 33 nodes to be scored (7864 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for midnightblue module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 435 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 10 nodes to be scored (0 eliminated genes)
##
## Level 10: 36 nodes to be scored (0 eliminated genes)
##
## Level 9: 62 nodes to be scored (306 eliminated genes)
##
## Level 8: 69 nodes to be scored (1298 eliminated genes)
##
## Level 7: 69 nodes to be scored (2619 eliminated genes)
##
## Level 6: 62 nodes to be scored (4684 eliminated genes)
##
## Level 5: 56 nodes to be scored (5858 eliminated genes)
##
## Level 4: 35 nodes to be scored (7111 eliminated genes)
##
## Level 3: 33 nodes to be scored (7864 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for black module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 406 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 11 nodes to be scored (0 eliminated genes)
##
## Level 10: 36 nodes to be scored (0 eliminated genes)
##
## Level 9: 58 nodes to be scored (332 eliminated genes)
##
## Level 8: 64 nodes to be scored (1315 eliminated genes)
##
## Level 7: 64 nodes to be scored (2628 eliminated genes)
##
## Level 6: 57 nodes to be scored (4662 eliminated genes)
##
## Level 5: 49 nodes to be scored (5832 eliminated genes)
##
## Level 4: 30 nodes to be scored (7105 eliminated genes)
##
## Level 3: 34 nodes to be scored (7861 eliminated genes)
##
## Level 2: 2 nodes to be scored (8124 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for pink module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 380 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 13: 1 nodes to be scored (0 eliminated genes)
##
## Level 12: 1 nodes to be scored (0 eliminated genes)
##
## Level 11: 8 nodes to be scored (24 eliminated genes)
##
## Level 10: 31 nodes to be scored (32 eliminated genes)
##
## Level 9: 50 nodes to be scored (282 eliminated genes)
##
## Level 8: 57 nodes to be scored (1226 eliminated genes)
##
## Level 7: 61 nodes to be scored (2592 eliminated genes)
##
## Level 6: 57 nodes to be scored (4686 eliminated genes)
##
## Level 5: 50 nodes to be scored (5824 eliminated genes)
##
## Level 4: 30 nodes to be scored (7075 eliminated genes)
##
## Level 3: 31 nodes to be scored (7862 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for magenta module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 313 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 1 nodes to be scored (0 eliminated genes)
##
## Level 10: 20 nodes to be scored (0 eliminated genes)
##
## Level 9: 47 nodes to be scored (31 eliminated genes)
##
## Level 8: 49 nodes to be scored (1026 eliminated genes)
##
## Level 7: 47 nodes to be scored (2285 eliminated genes)
##
## Level 6: 47 nodes to be scored (4406 eliminated genes)
##
## Level 5: 40 nodes to be scored (5683 eliminated genes)
##
## Level 4: 30 nodes to be scored (6998 eliminated genes)
##
## Level 3: 29 nodes to be scored (7852 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for purple module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 393 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 13: 1 nodes to be scored (0 eliminated genes)
##
## Level 12: 1 nodes to be scored (0 eliminated genes)
##
## Level 11: 9 nodes to be scored (24 eliminated genes)
##
## Level 10: 31 nodes to be scored (32 eliminated genes)
##
## Level 9: 52 nodes to be scored (294 eliminated genes)
##
## Level 8: 59 nodes to be scored (1253 eliminated genes)
##
## Level 7: 58 nodes to be scored (2632 eliminated genes)
##
## Level 6: 63 nodes to be scored (4655 eliminated genes)
##
## Level 5: 56 nodes to be scored (5710 eliminated genes)
##
## Level 4: 32 nodes to be scored (7094 eliminated genes)
##
## Level 3: 28 nodes to be scored (7864 eliminated genes)
##
## Level 2: 2 nodes to be scored (8124 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for greenyellow module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 377 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 13: 1 nodes to be scored (0 eliminated genes)
##
## Level 12: 1 nodes to be scored (0 eliminated genes)
##
## Level 11: 12 nodes to be scored (24 eliminated genes)
##
## Level 10: 32 nodes to be scored (32 eliminated genes)
##
## Level 9: 47 nodes to be scored (346 eliminated genes)
##
## Level 8: 52 nodes to be scored (1247 eliminated genes)
##
## Level 7: 61 nodes to be scored (2540 eliminated genes)
##
## Level 6: 59 nodes to be scored (4660 eliminated genes)
##
## Level 5: 50 nodes to be scored (5834 eliminated genes)
##
## Level 4: 28 nodes to be scored (7077 eliminated genes)
##
## Level 3: 31 nodes to be scored (7860 eliminated genes)
##
## Level 2: 2 nodes to be scored (8124 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for tan module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 352 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 6 nodes to be scored (0 eliminated genes)
##
## Level 10: 22 nodes to be scored (0 eliminated genes)
##
## Level 9: 45 nodes to be scored (164 eliminated genes)
##
## Level 8: 60 nodes to be scored (990 eliminated genes)
##
## Level 7: 53 nodes to be scored (2478 eliminated genes)
##
## Level 6: 55 nodes to be scored (4656 eliminated genes)
##
## Level 5: 43 nodes to be scored (5730 eliminated genes)
##
## Level 4: 32 nodes to be scored (7068 eliminated genes)
##
## Level 3: 33 nodes to be scored (7861 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for cyan module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 286 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 11 nodes to be scored (0 eliminated genes)
##
## Level 10: 17 nodes to be scored (0 eliminated genes)
##
## Level 9: 30 nodes to be scored (311 eliminated genes)
##
## Level 8: 38 nodes to be scored (843 eliminated genes)
##
## Level 7: 44 nodes to be scored (2196 eliminated genes)
##
## Level 6: 48 nodes to be scored (4446 eliminated genes)
##
## Level 5: 45 nodes to be scored (5630 eliminated genes)
##
## Level 4: 24 nodes to be scored (7042 eliminated genes)
##
## Level 3: 26 nodes to be scored (7846 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8198 eliminated genes)
## [1] "Significant CC terms for grey60 module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 250 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 13: 1 nodes to be scored (0 eliminated genes)
##
## Level 12: 1 nodes to be scored (0 eliminated genes)
##
## Level 11: 1 nodes to be scored (24 eliminated genes)
##
## Level 10: 12 nodes to be scored (32 eliminated genes)
##
## Level 9: 21 nodes to be scored (85 eliminated genes)
##
## Level 8: 34 nodes to be scored (874 eliminated genes)
##
## Level 7: 44 nodes to be scored (2030 eliminated genes)
##
## Level 6: 42 nodes to be scored (4462 eliminated genes)
##
## Level 5: 40 nodes to be scored (5655 eliminated genes)
##
## Level 4: 25 nodes to be scored (7009 eliminated genes)
##
## Level 3: 26 nodes to be scored (7834 eliminated genes)
##
## Level 2: 2 nodes to be scored (8124 eliminated genes)
##
## Level 1: 1 nodes to be scored (8204 eliminated genes)
## [1] "Significant CC terms for lightgreen module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 255 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 3 nodes to be scored (0 eliminated genes)
##
## Level 10: 8 nodes to be scored (0 eliminated genes)
##
## Level 9: 30 nodes to be scored (96 eliminated genes)
##
## Level 8: 40 nodes to be scored (535 eliminated genes)
##
## Level 7: 41 nodes to be scored (1972 eliminated genes)
##
## Level 6: 43 nodes to be scored (4362 eliminated genes)
##
## Level 5: 33 nodes to be scored (5680 eliminated genes)
##
## Level 4: 26 nodes to be scored (7045 eliminated genes)
##
## Level 3: 28 nodes to be scored (7837 eliminated genes)
##
## Level 2: 2 nodes to be scored (8125 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for lightyellow module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 220 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 11: 2 nodes to be scored (0 eliminated genes)
##
## Level 10: 15 nodes to be scored (0 eliminated genes)
##
## Level 9: 27 nodes to be scored (71 eliminated genes)
##
## Level 8: 32 nodes to be scored (930 eliminated genes)
##
## Level 7: 27 nodes to be scored (2035 eliminated genes)
##
## Level 6: 31 nodes to be scored (4143 eliminated genes)
##
## Level 5: 33 nodes to be scored (5286 eliminated genes)
##
## Level 4: 24 nodes to be scored (6986 eliminated genes)
##
## Level 3: 26 nodes to be scored (7827 eliminated genes)
##
## Level 2: 2 nodes to be scored (8123 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for royalblue module: 12"
##
## Building most specific GOs .....
## ( 1506 GO terms found. )
##
## Build GO DAG topology ..........
## ( 1726 GO terms and 2897 relations. )
##
## Annotating nodes ...............
## ( 8239 genes annotated to the GO terms. )
##
## -- Weight01 Algorithm --
##
## the algorithm is scoring 191 nontrivial nodes
## parameters:
## test statistic: fisher
##
## Level 10: 6 nodes to be scored (0 eliminated genes)
##
## Level 9: 16 nodes to be scored (0 eliminated genes)
##
## Level 8: 25 nodes to be scored (478 eliminated genes)
##
## Level 7: 31 nodes to be scored (1429 eliminated genes)
##
## Level 6: 36 nodes to be scored (3887 eliminated genes)
##
## Level 5: 30 nodes to be scored (5267 eliminated genes)
##
## Level 4: 21 nodes to be scored (6978 eliminated genes)
##
## Level 3: 23 nodes to be scored (7841 eliminated genes)
##
## Level 2: 2 nodes to be scored (8124 eliminated genes)
##
## Level 1: 1 nodes to be scored (8205 eliminated genes)
## [1] "Significant CC terms for darkred module: 12"6.2 Barplots
for(i in 1:length(modules)){
Plot <- topGOBarplot(ResCC[[i]]$ResSel, terms=12, pvalTh=0.01, title=modules[i], palette=NULL)
GOPlots$CC_Bar[[i]] <- Plot
names(GOPlots$CC_Bar)[i] <- modules[i]
}CCBar <- gridExtra::grid.arrange(GOPlots$CC_Bar$turquoise, GOPlots$CC_Bar$blue, GOPlots$CC_Bar$green, GOPlots$CC_Bar$brown,
GOPlots$CC_Bar$red, GOPlots$CC_Bar$midnightblue, GOPlots$CC_Bar$black, GOPlots$CC_Bar$pink,
GOPlots$CC_Bar$magenta, GOPlots$CC_Bar$purple, GOPlots$CC_Bar$greenyellow, GOPlots$CC_Bar$tan,
GOPlots$CC_Bar$cyan, GOPlots$CC_Bar$grey60, GOPlots$CC_Bar$lightgreen, GOPlots$CC_Bar$lightyellow,
GOPlots$CC_Bar$royalblue, GOPlots$CC_Bar$darkred,
ncol=4)
ggsave(file=paste0(OutputFolder, 'CCBarplot.pdf'), CCBar, width=25, height=25)
CCBar
## TableGrob (5 x 4) "arrange": 18 grobs
## z cells name grob
## 1 1 (1-1,1-1) arrange gtable[layout]
## 2 2 (1-1,2-2) arrange gtable[layout]
## 3 3 (1-1,3-3) arrange gtable[layout]
## 4 4 (1-1,4-4) arrange gtable[layout]
## 5 5 (2-2,1-1) arrange gtable[layout]
## 6 6 (2-2,2-2) arrange gtable[layout]
## 7 7 (2-2,3-3) arrange gtable[layout]
## 8 8 (2-2,4-4) arrange gtable[layout]
## 9 9 (3-3,1-1) arrange gtable[layout]
## 10 10 (3-3,2-2) arrange gtable[layout]
## 11 11 (3-3,3-3) arrange gtable[layout]
## 12 12 (3-3,4-4) arrange gtable[layout]
## 13 13 (4-4,1-1) arrange gtable[layout]
## 14 14 (4-4,2-2) arrange gtable[layout]
## 15 15 (4-4,3-3) arrange gtable[layout]
## 16 16 (4-4,4-4) arrange gtable[layout]
## 17 17 (5-5,1-1) arrange gtable[layout]
## 18 18 (5-5,2-2) arrange gtable[layout]7. Savings
SessionInfo <- sessionInfo()
Date <- date()
#save.image(paste0(OutputFolder, 'FunctionalWorkspace.RData'))Date## [1] "Tue Jul 22 18:47:37 2025"SessionInfo## R version 4.2.1 (2022-06-23)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.4 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
##
## 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=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] topGO_2.50.0 SparseM_1.81
## [3] GO.db_3.16.0 graph_1.76.0
## [5] org.Hs.eg.db_3.16.0 AnnotationDbi_1.60.0
## [7] SummarizedExperiment_1.28.0 Biobase_2.58.0
## [9] GenomicRanges_1.50.2 GenomeInfoDb_1.34.9
## [11] IRanges_2.32.0 S4Vectors_0.36.1
## [13] BiocGenerics_0.44.0 MatrixGenerics_1.10.0
## [15] matrixStats_0.63.0 viridis_0.6.2
## [17] viridisLite_0.4.1 ggplot2_3.4.1
## [19] dplyr_1.1.0
##
## loaded via a namespace (and not attached):
## [1] lattice_0.20-45 png_0.1-8 Biostrings_2.66.0
## [4] digest_0.6.31 utf8_1.2.3 R6_2.5.1
## [7] RSQLite_2.3.0 evaluate_0.20 highr_0.10
## [10] httr_1.4.5 pillar_1.8.1 zlibbioc_1.44.0
## [13] rlang_1.1.1 rstudioapi_0.14 jquerylib_0.1.4
## [16] blob_1.2.3 Matrix_1.5-3 rmarkdown_2.20
## [19] textshaping_0.3.6 stringr_1.5.0 RCurl_1.98-1.10
## [22] bit_4.0.5 munsell_0.5.0 DelayedArray_0.24.0
## [25] compiler_4.2.1 xfun_0.37 systemfonts_1.0.4
## [28] pkgconfig_2.0.3 htmltools_0.5.4 tidyselect_1.2.0
## [31] KEGGREST_1.38.0 tibble_3.2.1 gridExtra_2.3
## [34] GenomeInfoDbData_1.2.9 fansi_1.0.4 crayon_1.5.2
## [37] withr_2.5.0 bitops_1.0-7 grid_4.2.1
## [40] jsonlite_1.8.4 gtable_0.3.1 lifecycle_1.0.3
## [43] DBI_1.1.3 magrittr_2.0.3 scales_1.2.1
## [46] stringi_1.7.12 cli_3.6.1 cachem_1.0.7
## [49] farver_2.1.1 XVector_0.38.0 bslib_0.4.2
## [52] ragg_1.2.3 generics_0.1.3 vctrs_0.6.2
## [55] tools_4.2.1 bit64_4.0.5 glue_1.6.2
## [58] fastmap_1.1.1 yaml_2.3.7 colorspace_2.1-0
## [61] memoise_2.0.1 knitr_1.42 sass_0.4.5