Hi!
I want to know, is it possible to identify copy number variations from paired end RNA-seq data? if yes , how? and which tools to use?
What I have done till now is:
a) Executed mpileup on the bam file of paired end RNA-seq file.
b) Next I wanted to use varscan copynumber, but it requires normal_pileup and tumour pile-up. I only have pileup on my experimental data. Hence I cannot move forward or am I missing a trick here?
Please help
Thank you
2 answers
I have seen papers calling CNVs from RNA-seq data, albeit only the very large ones (chromosome arm-sized).
For example, have a look at Figure 1C and accompanying methods in this paper:
Patel et al. (2014) Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma
The only way to see CNVs with RNAseq is if some of the copies result in fusion events with other genes, thus resulting in one read in a pair aligning to gene A and the other to gene B. Aside from that, one can't look at CNVs with RNAseq.
Even with a matched control sample, you still can't use the method you outlined to call copy number. It's impossible to discriminate between differential expression and an underlying copy number variation with RNAseq data. This is a fundamental limitation. If you want to look at CNVs, you need to sequence DNA.
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Devon Ryan
Yes, you can call CNVs from WGBS data (I've never seen anyone do it, but there's no reason you couldn't). You could use the mpileup->varscan copy number method with that.
I take that back, while you can use WGBS data to call CNVs, varscan still needs a control dataset. You might be able to find something close enough in a public dataset, if you're lucky. Otherwise, there ends up being no great way to call CNVs. If one were to use the naive method of just going by depth, then any bias introduced by mappability, library construction, etc. could seriously skew the results. Having said that, if you're going to validate things anyway and you can tolerate a moderately high false-positive rate, then perhaps this can suffice.
Best of luck with this. Feel encouraged to leave a comment when you have the results. I'm curious to hear how well this works in practice.
True, if the CNV is absolutely huge like that then it can work.
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I just realized I started another thread with some options listed: Detecting copy number alterations based on RNA-seq data