Hi,
I am trying to run gage and FGNet with my local list. But I can't seems to make it works.
I have created a gmt file and read it with readList to a list structure. I converted the list elements into Entrez IDs. when I try to run the gage command I keep getting `NA`
This is what I'm doing
This all looks fine, but when I try to run the gage function, I get only NaN as a results.
When I run everything with the gage function kegg.gsets()
it works fine.
As far as I can tell, there is no difference in the structure between the two list. But somehow gage can't seems to find any hits in my list.
What am doing wrong here?
thanks
Assa
I am trying to run gage and FGNet with my local list. But I can't seems to make it works.
I have created a gmt file and read it with readList to a list structure. I converted the list elements into Entrez IDs. when I try to run the gage command I keep getting `NA`
This is what I'm doing
Code:
kegg_gsea <- readList("c2.cp.kegg.v4.0.symbols.gmt") #data set from the mSigDB kegg_gsea[1] $KEGG_GLYCOLYSIS_GLUCONEOGENESIS [1] "ACSS2" "GCK" "PGK2" "PGK1" "PDHB" "PDHA1" "PDHA2" [8] "PGM2" "TPI1" "ACSS1" "FBP1" "ADH1B" "HK2" "ADH1C" [15] "HK1" "HK3" "ADH4" "PGAM2" "ADH5" "PGAM1" "ADH1A" [22] "ALDOC" "ALDH7A1" "LDHAL6B" "PKLR" "LDHAL6A" "ENO1" "PKM2" [29] "PFKP" "BPGM" "PCK2" "PCK1" "ALDH1B1" "ALDH2" "ALDH3A1" [36] "AKR1A1" "FBP2" "PFKM" "PFKL" "LDHC" "GAPDH" "ENO3" [43] "ENO2" "PGAM4" "ADH7" "ADH6" "LDHB" "ALDH1A3" "ALDH3B1" [50] "ALDH3B2" "ALDH9A1" "ALDH3A2" "GALM" "ALDOA" "DLD" "DLAT" [57] "ALDOB" "G6PC2" "LDHA" "G6PC" "PGM1" "GPI" kegg_gsea_eg <- lapply(kegg_gsea_Up, sym2eg) # convert the file from gene symbols to entrez IDs ( human data). kegg_gsea_eg[1] $KEGG_GLYCOLYSIS_GLUCONEOGENESIS [1] "55902" "2645" "5232" "5230" "5162" "5160" "5161" "55276" [9] "7167" "84532" "2203" "125" "3099" "126" "3098" "3101" [17] "127" "5224" "128" "5223" "124" "230" "501" "92483" [25] "5313" "160287" "2023" "5315" "5214" "669" "5106" "5105" [33] "219" "217" "218" "10327" "8789" "5213" "5211" "3948" [41] "2597" "2027" "2026" "441531" "131" "130" "3945" "220" [49] "221" "222" "223" "224" "130589" "226" "1738" "1737" [57] "229" "57818" "3939" "2538" "5236" "2821"
Code:
kegg.gs.gsea <- gage(data.norm, gsets = kegg_gsea_eg, ref = ctrl, samp = cr2w, compare ="unpaired") > head(kegg.gs.gsea$greater) p.geomean stat.mean p.val q.val KEGG_GLYCOLYSIS_GLUCONEOGENESIS NA NaN NA NA KEGG_CITRATE_CYCLE_TCA_CYCLE NA NaN NA NA KEGG_PENTOSE_PHOSPHATE_PATHWAY NA NaN NA NA KEGG_PENTOSE_AND_GLUCURONATE_INTERCONVERSIONS NA NaN NA NA KEGG_FRUCTOSE_AND_MANNOSE_METABOLISM NA NaN NA NA KEGG_GALACTOSE_METABOLISM NA NaN NA NA set.size CR2Wo1 CR2Wo2 CR2Wo3 KEGG_GLYCOLYSIS_GLUCONEOGENESIS 0 NA NA NA KEGG_CITRATE_CYCLE_TCA_CYCLE 0 NA NA NA KEGG_PENTOSE_PHOSPHATE_PATHWAY 0 NA NA NA KEGG_PENTOSE_AND_GLUCURONATE_INTERCONVERSIONS 0 NA NA NA KEGG_FRUCTOSE_AND_MANNOSE_METABOLISM 0 NA NA NA KEGG_GALACTOSE_METABOLISM 0 NA NA NA CR2Wo4 CR2Wo5 CR2Wo6 KEGG_GLYCOLYSIS_GLUCONEOGENESIS NA NA NA KEGG_CITRATE_CYCLE_TCA_CYCLE NA NA NA KEGG_PENTOSE_PHOSPHATE_PATHWAY NA NA NA KEGG_PENTOSE_AND_GLUCURONATE_INTERCONVERSIONS NA NA NA KEGG_FRUCTOSE_AND_MANNOSE_METABOLISM NA NA NA KEGG_GALACTOSE_METABOLISM NA NA NA
it works fine.
Code:
>kegg.gs.gage$greater[1:4,] p.geomean stat.mean p.val mmu03010 Ribosome 0.0007681659 3.143027 1.394098e-14 mmu00982 Drug metabolism - cytochrome P450 0.0051657235 2.555047 4.341639e-10 mmu05204 Chemical carcinogenesis 0.0154393498 2.093465 2.108867e-07 mmu02010 ABC transporters 0.0164200321 2.079450 3.064449e-07 q.val set.size CR2Wo1 mmu03010 Ribosome 3.541008e-12 135 0.0007615765 mmu00982 Drug metabolism - cytochrome P450 5.513882e-08 58 0.0049954942 mmu05204 Chemical carcinogenesis 1.635328e-05 74 0.0169161660 mmu02010 ABC transporters 1.635328e-05 44 0.0071786706 CR2Wo2 CR2Wo3 CR2Wo4 mmu03010 Ribosome 0.004924298 0.001273332 0.0008053285 mmu00982 Drug metabolism - cytochrome P450 0.042250736 0.001703304 0.0045428924 mmu05204 Chemical carcinogenesis 0.093709197 0.009452226 0.0075235397 mmu02010 ABC transporters 0.001556945 0.021834009 0.0356210166 CR2Wo5 CR2Wo6 mmu03010 Ribosome 0.003067049 3.569067e-05 mmu00982 Drug metabolism - cytochrome P450 0.006710034 3.373549e-03 mmu05204 Chemical carcinogenesis 0.023693002 1.426880e-02 mmu02010 ABC transporters 0.032930730 1.248961e-01
What am doing wrong here?
thanks
Assa
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