Hi,
I would have thought that someone else had noticed this by now, but I have not been able to find this issue addressed elsewhere in this site...
Cufflinks seems to randomly drop FPKM values. For instance, my current dataset has 6 mouse RNAseq samples quantitated using tophat 1.4.0 / cufflinks 1.3.0, -G, Ensembl 63 gtf, no multireads. On average, 19% of the zero-fpkm genes in any sample will have a nonzero read count.
I quantify read counts using intersectBed to return read tallies on the nonredundant exonic space per gene, and verify presence of reads in the track files. So I can have genes with tens, even hundreds of thousands of reads, but zero fpkms.
Some genes are consistently high-count and zero-fpkm in all samples; others have fpkms in some samples but not others (while the RPMs are ~consistent across samples). The majority of affected genes are only dropped in a few samples, suggesting this is not a gene structure or annotation issue. In particular, the fairly consistent fraction of dropped fpkms per sample makes me wonder if it has something to do with the read-to-locus assigment algorithms.
I first noticed this effect in January of last year but brushed it off and assumed it would be fixed later on, but this hasn't been the case. This issue has appeared in three unrelated investigations since then (all mouse -- but I doubt that's the underlying issue ).
So to make a long story short, has anyone else noticed this, and if so what measures do you take to fill in lost FPKMs? Or do you just work with the counts instead?
Thanks,
Ariel
I would have thought that someone else had noticed this by now, but I have not been able to find this issue addressed elsewhere in this site...
Cufflinks seems to randomly drop FPKM values. For instance, my current dataset has 6 mouse RNAseq samples quantitated using tophat 1.4.0 / cufflinks 1.3.0, -G, Ensembl 63 gtf, no multireads. On average, 19% of the zero-fpkm genes in any sample will have a nonzero read count.
I quantify read counts using intersectBed to return read tallies on the nonredundant exonic space per gene, and verify presence of reads in the track files. So I can have genes with tens, even hundreds of thousands of reads, but zero fpkms.
Some genes are consistently high-count and zero-fpkm in all samples; others have fpkms in some samples but not others (while the RPMs are ~consistent across samples). The majority of affected genes are only dropped in a few samples, suggesting this is not a gene structure or annotation issue. In particular, the fairly consistent fraction of dropped fpkms per sample makes me wonder if it has something to do with the read-to-locus assigment algorithms.
I first noticed this effect in January of last year but brushed it off and assumed it would be fixed later on, but this hasn't been the case. This issue has appeared in three unrelated investigations since then (all mouse -- but I doubt that's the underlying issue ).
So to make a long story short, has anyone else noticed this, and if so what measures do you take to fill in lost FPKMs? Or do you just work with the counts instead?
Thanks,
Ariel
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