Is joint (combined genome+exome) FAF unreliable if either genome or exome fails filters?

General
1

I’m annotating my variants of interest using the published gnomad vcf’s. I intended to simply use the “fafmax_faf95_max_joint” INFO column subject to the FILTER column.

However, if the joint value includes both genome and exome data even if one fails filters, then I would want to look at only the “fafmax_faf95_max” column from the PASS data. Is my understanding correct?

2

@pgarg Thanks for posting this question, when creating the release data, we only filtered out chrM, AS_lowqual sites and AC_raw == 0 variants, but the FILTER column from variant QC (“PASS” or not) need to be interpreted with precaution by users, we would have some variants that didn’t PASS in both datasets due to different coverage.

3

Thanks again for your question!

As a follow-up, the VCF FILTER field has been updated in our v4.1 release to account for both exome and genome datasets, and variants are categorized in the FILTER column based on their status in both datasets. Here’s how the filtering works now:

  • “PASS”: The variant passed all filters in both exomes and genomes, or passed in one dataset while being absent from the other.
  • “EXOMES_FILTERED”: The variant failed QC in the exomes dataset but either passed in the genomes dataset or was not present in genomes. You can find more details about the failure in the exomes_filters field within the INFO column.
  • “GENOMES_FILTERED”: The variant failed QC in the genomes dataset but either passed in the exomes dataset or was not present in exomes. More details are available in the genomes_filters field in the INFO column.
  • “BOTH_FILTERED”: The variant failed QC in both exomes and genomes. You can refer to both exomes_filters and genomes_filters within the INFO column for more information.

Given this, it’s important to interpret the filtering based on your specific use case. If you’re focusing on high-confidence variants, you may want to restrict your analysis to “PASS” variants, or you can review the details in the exomes_filters and genomes_filters fields to better understand the filtering reasons.

I hope this clears things up! Please let me know if you have any other questions.