Hi,
I got a fpkm normalized RNAseq gene expression data. Really a lot of genes at some groups have expression value less than 1, that means after log2 transform, the value is negative. Some of the values even be -1000, which is really annoying.
How do you usually treat with this values, from my experience, log transformed RNAseq expression data never have negative values.
In these cases it's not unusual to add a pseudocount of 1 to all counts so genes with 0 return to 0 after log. Obviously you have to assume that adding 1 doesn't bias much the initial non-zero counts.
(EDIT: Apologies, this was meant to be a comment to question of how to treat genes with 0 counts)
Just for reference, a value of 0.25 (by default, it's the prior.count option) is added by edgeR before calculating log2 rpkm or cpm values. Whether this is needed or not depends on ones goals.
While it may be common to log(x+1) for RPKM / FPKM, this does not mean that it is statistically valid if your goal is differential expression analysis.
You treat negative values the same as positive ones. There's no reason to expect FPKM or TPM or CPM or even normalized counts to be greater than 1.
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Update October 15, 2018
Just to clarify something for others arriving here: logging RPKM or FPKM values does not make these any better for conducting statistical comparisons. With no cross-sample normalisation used when producing RPKM / FPKM, these units are not suitable for differential expression.
Please read this: A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis
Also, by Harold Pimental: What the FPKM? A review of RNA-Seq expression units