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Thread | Thread Starter | Forum | Replies | Last Post |
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#1 |
Member
Location: Paris Join Date: Sep 2009
Posts: 14
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Hi!
I'm begining to work on the SV/CNV dicovery field. I found many different methods to do this. The majority of them take as input mapped reads, but there is few documentation of the parameters that we must be used. For methods that analyse the paired mapping abnormalities, it seems that we must return all possible hits, and we must perform single end alignment even if we have paired end reads. For methods that analyse split read alignment, it seems that non gapped alignment is required and all hits must be returned. Very few programs speak about duplicated reads (must we removed them?), or masking reference genome (should we mask the reference before or after the mapping?). I'm not shure that there is one unique mapping process that may be used to all the SV CNV mehods, but have your point of view will may be inspired me!. So what software do you use for mapping and SV/CNV discovery and what parameters do you use for the mapping? I will begin my test with BWA ungapped and all possible hits (-n 600 -N 600) and I will see if there is different with the default parameters. Best regards Maria |
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#2 |
Member
Location: Cambridge area, UK Join Date: Jan 2010
Posts: 35
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Hi.
I think the answer to your question depends on the coverage you have. We have some experience with low coverage CNV detection in tumour samples. For us paired end is not useful (the only benefit is that we can map a few more reads, but it is not worth the extra cost/time) and we only use uniquely mapped reads. If you take the ratio of reads in a test and a control, that smooth out a lot of the biases (mailny mappability problem). Also GC correction is very important for some samples. I suspect the paramenters used for the alignant are not so crucial, as long as they are the same for test and control. |
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#3 | |
Junior Member
Location: Boston Join Date: Dec 2012
Posts: 6
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I am also very much interested in these questions. I have high coverage (~150x) paired end sequence of the yeast genome. Using default parameters in BWA, I seem to be missing most SV data. So far I have tried Retroseq to map insertions of specific elements. I can find some retrotransposons at their reference location, but not all of them, and nothing novel. I have certain gene constructs that I have inserted in the lab, and I cannot find these insertions in the data, but again I find only the endogenous loci.
Could someone explain a little bit more about the following BWA parameters, or suggest other things to change? Quote:
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Tags |
cnv, mapping, structural variation |
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