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Does anyone know how DESeq2 handles genes that have zero counts in one condition and >0 counts in another?
My results output shows that these genes have a positive log2 fold-change value, but I do not understand how DESeq2 arrives at this number if it is taking the log of a ratio, in which the numerator is divided by zero.
Count data (letters are conditions; numbers are replicates):
> dds <- DESeqDataSetFromMatrix(countData = countData, colData = colData, design = ~ condition) > dds$condition <- factor(dds$condition, levels=c("A","B")) > dds <- DESeq(dds) > res<-results(dds,independentFiltering = F)
I know that DESeq1 gave an 'Inf' value in these cases, but how does DESeq2 arrive at a real number value?