I am using DESeq2 to perform a differential expression analysis, but I obtained very strange results for some genes. For some genes, I have very high log2FoldChange with very low p-value as displayed in the following table.
When I look the normalized expression values for these genes. I can see that these genes are expressed in only one single sample (condition1= samples from 1 to 7, condition2 = samples 8 to 13).
Could you please tell me how to avoid DESeq2 to detect these genes as differentially expressed ?
I am using to following commands:
dds <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable, directory = directory, design= ~ condition) dds <- DESeq(dds) res <- results(dds, contrast=c("condition",condition1,condition2))