So after feature counts of RNA-seq bam file, I have an count file. I input the count file into DEseq, and got results which contain foldchange values such as 0/inf/NA, so how can I deal with these values when I want to use foldchange to filter out most up-/down- regulated genes?
So for foldchange == NA, I think this case can directly dropped. But what about foldchange ==0/inf?
Thank you.
id baseMean baseMeanA baseMeanB foldChange log2FoldChange pval padj
SOCS4 1834 2321 1348 0.580 -0.7844 0.00038 0.844
NPIPA3 34.1155 68.23175774754 0 0 Inf 7.51E-09 7.71E-05
AL627309.5 2.0225 0 4.045 Inf Inf 0.434 1
AP002833.2 0 0 0 NA NA NA NA
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Hi,
Inf and NA occurred due to 0 in one of the sample (baseMeanA or baseMeanB). The common practice to deal with this problem is to add small number (e.g. 0.1 ) to normalised expression value (e.g basemean/FPKM/RPKM) and recalculate the fold change.
It should be ok as you are adding small constant value to all the genes. Therefore, it nullifies any possibility of bias.
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