When I use DESeq code as below

sampleFiles <- grep("counts", list.files(directory),value=T) condition <- c("0W","1W","2W","3W","0W","1W","2W","3W","0W","1W","2W","3W") sampleTable <- data.frame(sampleName = sampleFiles, fileName = sampleFiles, condition = condition) sampleTable$condition <- factor(sampleTable$condition) ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable, directory = directory, design= ~ condition)

dds <- DESeq(ddsHTSeq) resultsNames(dds) res <- results(dds, alpha = 0.05, name = "condition_1W_vs_0W", lfcThreshold =1 )

I got a result like attaced picture

I got a 16 up-regulated gene from DESeq2 result.

However, when I count number of upregulated gene using excel with same threshold (paj<0.05, logfoldchange >1) I got a 211 up-regulated gene.

Do you know why the result of deg is different despite I used same thereshold?

Please understand that this forum is meant for technical help with the packages. Excel is none of it, and figuring out how to do proper filtering and manipulation in it is off-topic here. The answer can be that either your filtering or counting is wrong or that loading the output into Excel does some sort of conversion of numbers that skew the result, but digging that out is on you.