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GOtermAnalysis.R
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GOtermAnalysis.R
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library(dplyr)
library(topGO)
library(GO.db)
library(wordcloud)
library(GenomicRanges)
rm(list = ls())
specRefs = c("hg19", "mm10")
specQues = c("mm10","hg19")
gapType = "queIns"
gapNames = c("gain","loss","gain", "loss")
names(gapNames) <- c("refIns", "refDel", "queIns", "queDel")
for(spec in 1:2){
specRef = specRefs[spec]
specQue = specQues[spec]
for(gapType in names(gapNames)){
if(specRef == "hg19"){
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
library(org.Hs.eg.db)
org.db <- org.Hs.eg.db
}
if(specRef == "mm10"){
library(TxDb.Mmusculus.UCSC.mm10.knownGene)
txdb <- TxDb.Mmusculus.UCSC.mm10.knownGene
library(org.Mm.eg.db)
org.db <- org.Mm.eg.db
}
load(paste("~/Desktop/RTN_domains/R_objects/netsAnalysis/hotspots/", specRef, "repNoRep.RData", sep = ""))
load(paste("Desktop/RTN_domains/R_objects/netsAnalysis/syntheticBinnedGenome/", specRef, ".synthBin.RData",sep = ""))
load(paste("Desktop/RTN_domains/R_objects/netsAnalysis/shiftData/", specRef, ".expand.breaks.RData", sep = ""))
load(paste("~/Desktop/RTN_domains/R_objects/netsAnalysis/syntheticBinnedGenome/", specRef, "synthBinNorm.RData", sep = ""))
# both of these things work through entrez gene IDs
# now we can do the overlaps and get the necesary gene IDs
devtools::source_url("http://raw.githubusercontent.com/ReubenBuck/RTN_domains_scripts/master/comparativeGenomics/netScripts/netDataFunctions.R")
geneFeatures <- sort(sortSeqlevels(GenomicFeatures::genes(txdb)))
gene <- genoExpandBreak(geneFeatures, synthGenome = newSynthRefShift, seqlengths(synthBinNorm.gr))
if((gapType == "refDel" & specRef == "hg19") | (gapType == "queDel" & specRef == "mm10")){
sigRange <- repSigRanges[[gapType]]
}else{
sigRange <- GenomicRanges::intersect(repSigRanges[[gapType]], noRepSigRanges[[gapType]])
}
ol <- findOverlaps(gene, sigRange)
pInt <- pintersect(gene[queryHits(ol)], sigRange[subjectHits(ol)])
olWidth <- data.frame(pInt) %>%
group_by(gene_id) %>%
summarise(width = sum(width))
geneWidth <- width(GenomicFeatures::genes(txdb))
names(geneWidth) <- GenomicFeatures::genes(txdb)$gene_id
olWidth <- olWidth[olWidth$width/geneWidth[olWidth$gene_id] == 1,]
keys <- olWidth$gene_id
geneSymbol <- OrganismDbi::select(org.db, keys=keys, columns = c("SYMBOL","GO"))
# save the gene symbol info elsewhere
write.table(geneSymbol,quote = FALSE, sep = "\t",row.names = FALSE, col.names = TRUE,
file = paste("~/Desktop/RTN_domains/data/comparativeGenomics/hotspotsGenes/",
specRef,"_", gapType,"_","hotspotGenes.txt", sep = ""))
ol <- findOverlaps(gene, reduce(synthBinNorm.gr), type = "within")
allKeysNames <- gene$gene_id[queryHits(ol)]
allKeys <- rep(0, length(allKeysNames))
names(allKeys) <- allKeysNames
allKeys[keys] = 1
sigGene <- function(allGene){
return(allGene == 1)
}
if(specRef == "hg19"){
sampleGOdata <- new("topGOdata",
description = "Simple session", ontology = "BP",
allGenes = allKeys,
geneSel = sigGene,
nodeSize = 10,
mapping = "org.Hs.eg.db",
annotationFun = annFUN.org
)
}
if(specRef == "mm10"){
sampleGOdata <- new("topGOdata",
description = "Simple session", ontology = "BP",
allGenes = allKeys,
geneSel = sigGene,
nodeSize = 10,
mapping = "org.Mm.eg.db",
annotationFun = annFUN.org
)
}
resultFisher <- runTest(sampleGOdata, algorithm = "classic", statistic = "fisher")
resultElim <- runTest(sampleGOdata, algorithm = "elim", statistic = "fisher")
resultWeight <- runTest(sampleGOdata, algorithm = "weight", statistic = "fisher")
resultParentChild <- runTest(sampleGOdata, algorithm = "parentchild", statistic = "fisher")
resMethod <- c("classicFisher", "elimFisher","weightFisher" ,"parentChildFisher")
allRes <- NULL
for(i in resMethod){
res <- GenTable(sampleGOdata, classicFisher = resultFisher, elimFisher = resultElim,
weightFisher = resultWeight, parentChildFisher = resultParentChild,
topNodes = length(score(resultFisher)),orderBy = i)
allRes <- c(allRes, list(res))
}
names(allRes) <- resMethod
cFisher <- allRes$classicFisher
save(cFisher, file = paste("~/Desktop/RTN_domains/R_objects/netsAnalysis/goLists/",specRef, gapType,"GoTermLists.RData",sep = "") )
algo <- c("Elim", "Weight", "ParentChild")
algoName <- c("elim", "weight", "parent child")
names(algoName) <- algo
algoName <- c("classic", algoName)
names(algoName) <- resMethod
printResAll <- NULL
for(i in resMethod){
printRes <- data.frame(Algorithm = c(algoName[i], rep("",9)),
allRes[[i]][1:10,c("GO.ID", "Term", "Significant", "Expected", i)])
rownames(printRes) <- NULL
colnames(printRes)[ncol(printRes)] <- "p-value"
printResAll <- rbind(printResAll,printRes)
}
# now we can give these name
# labels and captions
xTab <- xtable::xtable(printResAll,
caption = paste("Top 10 biological process GO terms for genes located in", specRef, gapNames[gapType], "hotspots.",
"P-values for each GO term were calculated using the fisher statistic combined with one of four separate algorithms that each take the GO hierarchy into account (described in methods)"),
label = paste("tab:",specRef,gapType,"goTerm", sep = ""))
termTab <- print(xTab,include.rownames = FALSE, hline.after = c(0,0,10,20,30))
fileConn<-file(paste("~/Desktop/RTN_domains/RTN_domain_plots/netGainLoss/goTables/",specRef, gapType,"GoTermTab.tex",sep = ""))
writeLines(termTab, fileConn)
close(fileConn)
}
}