Hi there,

I noticed a discrepancy with cascading effects when I followed the instruction. During DE analysis, a file called "WT.C_v_WT.NC.txt" is generated and used during pathway analysis:

DE_Analysis_mm.md

9. Write top.table to a file, adding in cpms and annotation

top.table$Gene <- rownames(top.table)
top.table <- top.table[,c("Gene", names(top.table)[1:6])]
top.table <- data.frame(top.table,anno[match(top.table$Gene,anno$Gene.stable.ID),],logcpm[match(top.table$Gene,rownames(logcpm)),])

head(top.table)

                         Gene            logFC   AveExpr       t       P.Value
ENSMUSG00000020608 ENSMUSG00000020608 -2.494152 7.871119 -44.93189 1.633862e-19
ENSMUSG00000052212 ENSMUSG00000052212  4.544592 6.203043  40.16863 1.138575e-18
ENSMUSG00000049103 ENSMUSG00000049103  2.155498 9.892016  40.16019 1.142725e-18
ENSMUSG00000030203 ENSMUSG00000030203 -4.127795 7.005929 -34.51508 1.565016e-17
ENSMUSG00000027508 ENSMUSG00000027508 -1.906200 8.124895 -33.88940 2.145300e-17
ENSMUSG00000021990 ENSMUSG00000021990 -2.682202 8.368960 -33.73316 2.323138e-17

write.table(top.table, file = "WT.C_v_WT.NC.txt", row.names = F, sep = "\t", quote = F)

enrichment_mm.md

1. topGO Example - Using Kolmogorov-Smirnov Testing

Our first example uses Kolmogorov-Smirnov Testing for enrichment testing of our mouse DE results, with GO annotation obtained from the Bioconductor database org.Mm.eg.db.

The first step in each topGO analysis is to create a topGOdata object. This contains the genes, the score for each gene (here we use the p-value from the DE test), the GO terms associated with each gene, and the ontology to be used (here we use the biological process ontology)

infile <- "WT.C_v_WT.NC.txt"
tmp <- read.delim(infile)
geneList <- tmp$P.Value
xx <- as.list(org.Mm.egENSEMBL2EG)
names(geneList) <- xx[sapply(strsplit(tmp$Gene,split="\."),"[[", 1L)]
head(geneList)

     74127        70686        14268        20112        67241        66775 
 9.057118e-18 3.288834e-17 6.570900e-17 6.921801e-17 2.519371e-16 2.746416e-16

I believe two different files called WT.C_v_WT.NC.txt are used because their p-values are not consistent in the above two .md files. (compare last column P.value in the first .md file and the 2nd line in the second .md file) I think this issue has some bad consequences as all the downstream analyses are affected and I could not reproduce the results. As I cannot find any files called WT.C_v_WT.NC.txt on GitHub, I would appreciate it if you confirm and resolve this issue.

Best wishes,
Yige