What tools could be used for false positive filtering of somatic variants called? And how do they work?
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2.3 years ago
Laven9 • 0

I am now confusing about false positive filtering of my called SNVs. I am wondering how do you do the filtering? What tools to use? Should I use two different tools to call and use the SNVs in both calling as the true SNVs? What I used for SNV calling was Varscan2. But my files failed the fpfilter.py as all the variants failed like this:

0 passed filters
194 failed filters
        0 failed because no readcounts were returned
        35 failed minimim variant count < 3
        7 failed minimum variant freq < 0.05
        0 failed minimum strandedness < 0.0
        194 failed minimum reference readpos < 0.2
        194 failed minimum variant readpos < 0.15
        194 failed minimum reference dist3 < 0.2
        194 failed minimum variant dist3 < 0.15
        0 failed maximum reference MMQS > 50
        0 failed maximum variant MMQS > 100
        0 failed maximum MMQS diff (var - ref) > 50
        26 failed maximum mapqual diff (ref - var) > 10
        40 failed minimim ref mapqual < 20
        55 failed minimim var mapqual < 30
        0 failed minimim ref basequal < 15
        111 failed minimim var basequal < 30
        0 failed maximum RL diff (ref - var) > 0.05
next-gen • 437 views
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And actually, when I set --min-var-readpos 0 --min-ref-readpos 0 --min-var-dist3 0 --min-ref-dist3 0 , I got a result as :

194 variants in input file
194 had a bam-readcount result
194 had reads1>=2
0 passed filters
194 failed filters
        0 failed because no readcounts were returned
        60 failed minimim variant count < 4
        7 failed minimum variant freq < 0.05
        36 failed minimum strandedness < 0.01
        0 failed minimum reference readpos < 0.1
        0 failed minimum variant readpos < 0.1
        0 failed minimum reference dist3 < 0.1
        0 failed minimum variant dist3 < 0.1
        0 failed maximum reference MMQS > 100
        0 failed maximum variant MMQS > 100
        0 failed maximum MMQS diff (var - ref) > 50
        1 failed maximum mapqual diff (ref - var) > 50
        29 failed minimim ref mapqual < 15
        21 failed minimim var mapqual < 15
        0 failed minimim ref basequal < 15
        20 failed minimim var basequal < 15
        0 failed maximum RL diff (ref - var) > 0.25

The amount of fails are 174 < total 194, but it still reported 0 pass filters

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