I've performed my DEseq2 analysis on my samples. However, when I take a look at the resulting output, all of my p-adjusted values are the same for all genes and are equal to 0.9999068. Does this mean I have created an error upstream of analysis?
Also when I take a look at the summary of the results the LFC up and down as 0 for both. Does this indicate no significant log fold changes?
I'd really appreciate any advice on this please.
# deseq2 analysis design dds1 <- DESeqDataSetFromMatrix(countData = countdata, colData = colData, design = ~ Treatment) # subset Athero samples dds1c <- dds1b[,dds1b$Sample == "Athero"] # set untreated as reference for differential gene expression dds1c$Treatment <- relevel(dds1c$Treatment, ref = "untreated") # Run Deseq2 FCdds <- DESeq(dds1c) # View results of deseq2 data output resFC <- results(FCdds) # View summary of deseq2 data output summary(resFC) out of 17755 with nonzero total read count adjusted p-value < 0.1 LFC > 0 (up) : 0, 0% LFC < 0 (down) : 0, 0% outliers  : 24, 0.14% low counts  : 0, 0% (mean count < 0)  see 'cooksCutoff' argument of ?results  see 'independentFiltering' argument of ?results