I have a matrix with SAGE count data and i want to test for GO enrichment en Pathway enrichment. Therefore I want to use the globaltest in R. My data looks like this:
data_file
KI_1 KI_2 KI_4 KI_5 KI_6 WT_1 WT_2 WT_3 WT_4 WT_6
ENSMUSG00000002012 215 141 102 127 138 162 164 114 188 123
ENSMUSG00000028182 13 5 13 12 8 10 7 13 7 14
ENSMUSG00000002017 111 72 70 170 52 87 117 77 226 122
ENSMUSG00000028184 547 312 162 226 280 501 603 407 355 268
ENSMUSG00000002015 1712 1464 825 1038 1189 1991 1950 1457 1240 883
ENSMUSG00000028180 1129 944 766 869 737 1223 1254 865 871 844
The rownames contains ensembl gene IDs and each column represent a sample. These samples can be divided in two groups for testing pathway enrichment: KI1 and the WT2 group
groups <- c("KI1","KI1","KI1","KI1","KI1","WT2","WT2","WT2","WT2","WT2")
I found the function gtKEGG to do the pathway analysis, but my question is how? Because when I run the function I don't create any error but my output file is like this:
> gtKEGG(groups, t(data_file), annotation="org.Mm.eg.db")
holm alias p-value Statistic Expected Std.dev #Cov
00380 NA Tryptophan metabolism NA NA NA NA 0
01100 NA Metabolic pathways NA NA NA NA 0
02010 NA ABC transporters NA NA NA NA 0
04975 NA Fat digestion and absorption NA NA NA NA 0
04142 NA Lysosome NA NA NA NA 0
04012 NA ErbB signaling pathway NA NA NA NA 0
04110 NA Cell cycle NA NA NA NA 0
04360 NA Axon guidance NA NA NA NA 0
Can anyone help me with this question? Thanks! :)