Hi friends I use DESeq2 for differential expression analysis for HTSeq read count data with about 20000 genes. my genes have ENSEMBL ID. I have 44 patients (2 groups each with 22 patients) The result shows p-adjust all 0.9. Why is that? How can I fix it?
The code I use is this:
## Reading in raw data rdata <- read.table("my_data.txt", header = TRUE, row.names = 1) library(DESeq2) ## Create metadata sample_org <- data.frame(row.names = colnames(rdata), c(rep("0", 22), rep("1", 22))) colnames(sample_org) <- c("Group") dds <- DESeqDataSetFromMatrix(countData = rdata, colData = sample_org, design = ~Group) dd <- DESeq(dds) res <- results(dd) write.csv(res,"res.csv")
Also in this line of code I get this warning message from Rstudio but I do not think it affects my result:
dds <- DESeqDataSetFromMatrix(countData = rdata, colData = sample_org, design = ~Group) Warning message: In DESeqDataSet(se, design = design, ignoreRank) : some variables in design formula are characters, converting to factors