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Genomic Enrichment Analysis by Thalia Lake

Perform Gene Ontology Enrichment Analysis using R code by Thalia Lake to identify over-represented biological processes, molecular functions, and cellular components in gene clusters. Generate HTML reports for conditional tests.

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Genomic Enrichment Analysis by Thalia Lake

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  1. Gene Ontology Enrichment Analysis code By Thalia Lake

  2. setwd("/Users/StarTCL/Documents/R") • library("org.Mm.eg.db") • library("GOstats") • universe=read.csv("universereal.txt",header=T,sep='\t') • Touniverse=universe$To • universestrings=as.character(Touniverse) • checkGO=mget(universestrings,org.Mm.egGO,ifnotfound=NA) • hasGO=checkGO[!is.na(checkGO)] • geneid=names(hasGO) • MmCutoff=0.05 • setwd("clusters")

  3. myFiles=list.files(pattern="EntrezCluster.*out$") • for(f in myFiles){ • cluster=read.table(f,header=T) • cluster=unlist(cluster) • cstrings=as.character(cluster) • checkGOc=mget(cstrings,org.Mm.egGO,ifnotfound=NA) • hasGOc=checkGOc[!is.na(checkGOc)] • geneidc=names(hasGOc) • settings=c("BP","MF","CC")

  4. for(s in settings){ • params=new("GOHyperGParams", • geneIds=geneidc, • universeGeneIds=geneid, • annotation="org.Mm.eg.db", • ontology=s, • pvalueCutoff=MmCutoff, • conditional=FALSE, • testDirection="over")

  5. paramsCond=new("GOHyperGParams", • geneIds=geneidc, • universeGeneIds=geneid, • annotation="org.Mm.eg.db", • ontology=s, • pvalueCutoff=MmCutoff, • conditional=TRUE, • testDirection="over")

  6. MmOver=hyperGTest(params) • MmCondOver=hyperGTest(paramsCond) • MmOver • MmCondOver • df=summary(MmOver) • names(df) • outputfile=sprintf("%s_%s.html", f, s) • htmlReport(MmCondOver,file=outputfile) • df[df$OddsRatio>2, ] • }}

  7. Example of output data • Gene to GO CC Conditional test for over-representation

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