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Developed in the Data Sciences Platform at the Broad Institute, the toolkit offers a wide variety of tools with a primary focus on variant discovery and genotyping. Its powerful processing engine and high-performance computing features make it capable of taking on projects of any size. Learn more

Hard-filtering germline short variants Follow

4 comments

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    Bhoom Suktitipat

    As of today, some of the images on this post do not show up. I checked the links of these images and they appeared to be in "Google Drive"

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    Chase He

    Hi all, in brief, the recommended thresholds for getting passed variants are QD<2.0, FS>60.0, SOR>3.0, MQ<40.0, MQRankSum < -12.5 and ReadPosRankSum < -8.0. Am I right?

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    NawarDalila

    Chase He yes this is right.

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    Marsha Wallace

    This is a great overview of filtering parameters.

    It would be useful to contextualize how the hard filter recommendations in this article differ between SNPs vs INDELs as seen in: https://gatk.broadinstitute.org/hc/en-us/articles/360035531112--How-to-Filter-variants-either-with-VQSR-or-by-hard-filtering

    Some key differences listed in that article include:

    Filter

    SNP

    INDEL

    FS

    > 60

    > 200

    ReadPosRankSum

    < -8.0

    < -20.0

    QUAL

    < 30.0

    < 30.0

    SOR

    > 3.0

    NONE

    MQ

    < 40.0

    NONE

    MQRankSum

    < -12.5

    NONE

    Noticeably, a QUAL < 30.0 is recommended in the other hard filtering article for both SNPs and INDELs, but here it's indicated that 'For filtering purposes it is better to use QD than QUAL directly'.

    It would be useful to have a bit more in-depth explanation in this article about the SNP vs INDEL differences in filtering threshold recommendations.

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