Question: Significance Of Pindel'S "Ad" And Finding Svs In Igv
0
gravatar for Opulcy
4.3 years ago by
Opulcy0
Opulcy0 wrote:

Hi All,

I am running pindel on some nextgen data for exploring ins, del, rpl, tandem:dup, etc. I have two questions:

  1. I can see most of the deletions from pindel produced by the same bam files in IGV. However, I do not see most of the insertions and replacements. Can you please tell me why is that so? Are they false positive produced by pindel? Or, does IGV has a different way of predicting ins/dels/rpls than pindel? I am using all default parameters.

  2. I know AD = "Allele depth, how many reads support this allele". Can I filter out SVs based upon AD? I found a real deletion (confirmed by sanger sequencing) predicted by pindel with AD = 8! Whereas, there are some deletions which have far more reads but turned out to be false positives. Why is that so? What happens if pindel shows AD = 0. Does that mean that the prediction is unreliable as there are no reads to support that prediction?

Sorry for so many questions. But I am banging my head for weeks to look for answers over different forums and couldn't get hold of it.

Thanks in advance.

Regards

pindel cnv igv • 1.9k views
ADD COMMENTlink modified 4.2 years ago by Biostar ♦♦ 20 • written 4.3 years ago by Opulcy0
1

This question was also asked on SEQanswers: http://seqanswers.com/forums/showthread.php?p=108874

ADD REPLYlink written 4.3 years ago by nnutter200
0
gravatar for Opulcy
4.3 years ago by
Opulcy0
Opulcy0 wrote:

Does anyone have the answer for it? Not like the stupid one I got so far, please.

ADD COMMENTlink written 4.3 years ago by Opulcy0
0
gravatar for liangkaiye
4.3 years ago by
liangkaiye250
United States
liangkaiye250 wrote:

Pindel re-align every read, which does not have perfect match to the reference genome: unmapped, gaped aligned, clipping, with too many mismatches and so on. IGV is just visualizing alignment produced by the aligner so that any indels missed by the primary aligner would not appear in IGV.

you should look at the AD and also the total coverage for germline calling/filtering. a simple way is to calculate the percentage of alt supporting reads. say you see 10 reads support ref and 8 alt, this is a good het call. however if you see 1000 reads support ref, and again 8 for alt, you probably won't consider it as germline het.

If you run Pindel on one sample, you won't see any variants without reads supporting alt. but you will see them when you have multiple samples.

ADD COMMENTlink written 4.3 years ago by liangkaiye250
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