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--- mkatari-bioinformatics-august-2013-loadingphytozome [2015/06/18 06:27] – mkatari
+++ mkatari-bioinformatics-august-2013-loadingphytozome [2015/06/18 09:05] – mkatari
@@ Line 25: / Line 25: @@
 ===== Run Fisher Exact Test =====
- If you do not have a sample gene list to work with, simply create a random one.
+Let's use the significant genes identified from Deseq as our example. [[https://drive.google.com/file/d/0B172nc4dAaaOM2hvSlZWNG10UW8/view?usp=sharing|resSig]]
 <code>
-gene.list<-names(gene2go)[sample(1:length(names(gene2go)), 500)]
+gene.list<-read.table("resSig.txt", header=T)
 </code>
@@ Line 38: / Line 40: @@
 goterm_annot<-read.table("goterm_annot", sep="|", strip.white=TRUE,
                           row.names=1, quote="")
-goresults=doFisherTest(gene.list, goAnnot=goterm_annot)
+goresults=doFisherTest(as.character(gene.list[,1]), goAnnot=goterm_annot)
-write.table(goresults, "goresults", quote=F, sep="\t")
+write.table(goresults, "goresults.xls", col.names=NA, quote=F, sep="\t")
 </code>
+Visualizing your results in the GO-term graph. Use the RamiGO package. Simply provide the GO terms that are enriched and the corresponding p-value for the go-terms. By default it will save a file to your working directory called RamiGO.png
+<code>
+source("http://bioconductor.org/biocLite.R")
+biocLite("RamiGO")
+library(RamiGO)
+getAmigoTree(rownames(gotermresults)[1:3], c("blue","red","green"),gotermresults$AdjPval[1:3])
+</code>