My data is human not mouse
Hi All
While printing my pathways, if I print my gobpres, many pathways are Nulls, do you know what is the reason of this?
gobpres = gage(foldchanges, gsets=kegg.gs, same.dir= FALSE, compare ="unpaired")
gobpres, the first 2 rows have values, and the rest is NA, should I exclude them:
"","greater.p.geomean","greater.stat.mean","greater.p.val","greater.q.val","greater.set.size","greater.exp1","stats.stat.mean","stats.exp1"
"hsa00230 Purine metabolism",0.394537571882584,0.272307535746925,0.394537571882584,0.789075143765169,10,0.394537571882584,0.272307535746925,0.272307535746925
"hsa00190 Oxidative phosphorylation",0.878308066880623,-1.22573555096318,0.878308066880623,0.878308066880623,11,0.878308066880623,-1.22573555096318,-1.22573555096318
"hsa00010 Glycolysis / Gluconeogenesis",NA,NA,NA,NA,2,NA,NA,NA
"hsa00020 Citrate cycle (TCA cycle)",NA,NA,NA,NA,1,NA,NA,NA
"hsa00030 Pentose phosphate pathway",NA,NA,NA,NA,1,NA,NA,NA
Thanks
1 answer
I've seen this point of view:
http://seqanswers.com/forums/archive/index.php/t-51012.html
"mSigDB gene sets are human data, not mouse. Therefore, there won’t be any human gene sets mappable or enriched in your mouse data. Please always make sure the species and gene ID types are the same for your data and the gene set data as described in the Common Errors section of the gage tutorial. You can always use kegg.gsets() and go.gsets() in gage package to derive the latest KEGG pathway or GO gene sets. Actually it is recommended to do so even for human data because the gene sets in mSigDB may not be up-to-date. Please check gage package documentations for details: http://bioconductor.org/packages/release/bioc/html/gage.html
BTW, to convert gene symbol or other IDs to Entrez Genes, you can use id2eg() function in pathview package for the major research species. Function sym2eg() in gage package works for human genes only. For more details, please check the pathview package: http://bioconductor.org/packages/release/bioc/html/pathview.html"
See also this biostars post:
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I collided with the same problem. And I solved it by using ENTREZ gene ID as a gene names.