Hi
I've read a few number of papers about this topic such:
I'm surprised about the results, for example, when comparing coding sites in WES, RNA-seq only finds about 33% of SNP. When compared with WGS the percentage rises up to 45%, but still quite low (I think).
The specificity of these methods are not bad, the sensitivity is not so good (depends of coverage).
I'm surprised (I'm newbie) by what I think these are poor results, I would expect that at least for expressed regions the % of SNP found to be higher. I'm also surprised by the fact that most papers conform with coverages of 10x or even 3x to try to call for a variant when by being RNA-seq coverage souldn't be big deal.
I understand that some aligners can work with splice junctions, so this should not be a problem for variant calling with RNA-seq data.
I don't know if anyone can give me some clues or some more info about this. I'm just wondering about this.
Any paper where same samples are compared by using WGS, WES and RNA-seq?
Thanks
I've read a few number of papers about this topic such:
I'm surprised about the results, for example, when comparing coding sites in WES, RNA-seq only finds about 33% of SNP. When compared with WGS the percentage rises up to 45%, but still quite low (I think).
The specificity of these methods are not bad, the sensitivity is not so good (depends of coverage).
I'm surprised (I'm newbie) by what I think these are poor results, I would expect that at least for expressed regions the % of SNP found to be higher. I'm also surprised by the fact that most papers conform with coverages of 10x or even 3x to try to call for a variant when by being RNA-seq coverage souldn't be big deal.
I understand that some aligners can work with splice junctions, so this should not be a problem for variant calling with RNA-seq data.
I don't know if anyone can give me some clues or some more info about this. I'm just wondering about this.
Any paper where same samples are compared by using WGS, WES and RNA-seq?
Thanks
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