Calling tumor CNVs without normal as control?

ymc · 11-04-2013, 11:34 PM

http://www.foundationone.com/about-f..._Technical.pdf

I noticed that the recently IPOed Foundation Medicine only used tumor sample to find mutations, CNVs and rearrangements by sequencing 200+ genes panel.

I think their approach is fine with mutations/indels but sequencing normal as well to differentiate the true somatic ones might be slightly better. For rearrangement/fusion genes, they are using some introns sequence for that. I think RNA-seq can cover more fusion cases than this approach, is that right?

The only thing that bugs me a lot is their claim about CNVs. Isn't that without the normal control, GC bias can't be removed?

bw. · 11-05-2013, 02:11 AM

Also curious about this. Perhaps they are using pooled normals?
If library prep & sequencer are the same, and the pooled samples are copy-number neutral, it should be possible to get decent results using ExomeCNV.

ymc · 11-06-2013, 02:36 AM

Quote:

Originally Posted by bw.

Also curious about this. Perhaps they are using pooled normals?
If library prep & sequencer are the same, and the pooled samples are copy-number neutral, it should be possible to get decent results using ExomeCNV.

If I understand correctly, pooled normal only helps for calling CNVs on normal samples in the context of ExomeCNV.

I presume they aren't very nosy about accuracy. As long as it works in their clinical trials, then it is ok. One error can bite their ass though....

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11-04-2013, 11:34 PM	#1
ymc Senior Member Location: Hong Kong Join Date: Mar 2010 Posts: 498	Calling tumor CNVs without normal as control? http://www.foundationone.com/about-f..._Technical.pdf I noticed that the recently IPOed Foundation Medicine only used tumor sample to find mutations, CNVs and rearrangements by sequencing 200+ genes panel. I think their approach is fine with mutations/indels but sequencing normal as well to differentiate the true somatic ones might be slightly better. For rearrangement/fusion genes, they are using some introns sequence for that. I think RNA-seq can cover more fusion cases than this approach, is that right? The only thing that bugs me a lot is their claim about CNVs. Isn't that without the normal control, GC bias can't be removed?

11-05-2013, 02:11 AM	#2
bw. Member Location: San Francisco, CA Join Date: Mar 2012 Posts: 21	Also curious about this. Perhaps they are using pooled normals? If library prep & sequencer are the same, and the pooled samples are copy-number neutral, it should be possible to get decent results using ExomeCNV.