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how to run VQSR for individually called samples for rare variant discovery

We are running GATK HaplotypeCaller on ~50 whole exome samples. We are interested in rare variants - so we ran GATK in single sample mode instead of multi sample as you recommend, however we would like to take advantage of VQSR. What would you recommend? Can we run VQSR on the output from GATK single sample?

Additionally, we are likely to run extra batches of new exome samples. Should we wait until we have them all before running them through the GATK pipeline?

Many thanks in advance.

Best Answers


  • ledwardsledwards LondonMember

    Thanks for your response. I read here that I should run samples individually

    Sounds like the advice has changed?

    We also run targeted re sequencing in single sample mode for this reason (v rare variant detection), should we run multi sample for them too? Then apply hard filters?

  • Thank you for your valuable feedback. For small-N samples (e.g. proband only or trio data) we are continuing to run samples in multisample mode and using VQSR. I understand however, that best practices recommends running at least >30 samples together to obtain the best call-set. However, does this recommendation hold for high-coverage data? With high-coverage data and small-N sample sets (sometimes single sample), would you recommend using VQSR with additional sample-specific filtering criteria to help identify FPs?

    I am also curious if you could give a brief description of the new functionality for incremental processing. Would this improve the performance of VQSR even with single samples? Any preview would be great!

  • As a followup, for high-coverage but small-N experiments, would reducing the number of clusters (ie. adding --maxGaussians 4) still be recommended?

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