Hi, I hope that someone can be so gentle to help me. I'm analizing some data from RNA-Seq with TopHat and Cufflinks and I focus my attention on differently spliced genes. In particular, now I'm working on "maybe false positive", for example:
NM_001130171 Zfp207 Zfp207 chr11:80196780-80219375 day0 day3 OK 0.0000000 36.6325000 1.79769e+308 1.79769e+308 2.67658e-19 1.72370e-18 yes
this row comes from isoform_exp.diff file and the log2fold change is totally crazy because one sample is zero. So, I control the expression with expressionBarplot from cummeRbund, and the fpkm value of sample one was not zero! This function takes the information from another file, gene_exp.diff:
Zfp207 chr11:80196780-80219375 day0 day3 OK 26.4421 97.6658 1.88502 -15.6715 0 0 yes
The two files should be have the same results, but they are different and a p-value=0 is really strange.
Have someone some information about this? There is some normalization not explained in Cufflinks web site? What is the final true fpkm value?
Thanks :)
2 answers
Nothing strange, actually. The log2fold change is a very large number because log N/0 = Inf. They just decided to approx Inf with a very large number. If you use gene_exp.diff you can obtain different expression values than isoform_exp.diff (even for the same gene) if cufflinks finds some evidence of alternative splicing, so no surprise. On the cufflinks website they explain their normalization method. Good luck!
Thank you for the answer.
Log in to answer this question.
