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Deepvariant requires additional cli option for recalibrated BAM files #682

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marchoeppner opened this issue Jul 22, 2022 · 0 comments
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bug Something isn't working good first issue Good for newcomers
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Description of the bug

Currently, Sarek produces BAM files for variant calling through the GATK best-practices, including recalibration (default).

For DeepVariant, this is discouraged, as stated by the developers:

https://github.com/google/deepvariant/blob/r1.4/docs/trio-merge-case-study.md

It is recommended to use BAM files with original quality scores. In the case that BAM files went through recalibration, optional DV flags can be used in order to use original scores: --parse_sam_aux_fields, --use_original_quality_scores.

While recalibration can be disabled globally within Sarek, this would potentially have a negative impact on e.g. the GATK subworkflow, where recalibration is still considered to be useful (not sure it really is...).

Solution:

  1. Easy: Have an optional parameter in the Deepvariant module that sets the above flags if recalibration was performed
  2. Slighty less easy: Emit both deduped and deduped+recalibrated BAM/CRAM files after the GATK BP alignment/deduping and pass them to the appropriate subworkflows, i.e. GATK gets the recal BAM file, all other subworkflows get the non-recalibrated BAM. This might be the better choice in the long-term, depending on what the effect of recalibration is on other callers/tools (largely unexplored, I think).

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@marchoeppner marchoeppner added the bug Something isn't working label Jul 22, 2022
@maxulysse maxulysse added this to the 3.1 milestone Jul 22, 2022
@maxulysse maxulysse modified the milestones: 3.1, 3.2 Nov 23, 2022
@FriederikeHanssen FriederikeHanssen moved this to Todo (Hackathon General) in nf-core Hackathon March 2023 Mar 21, 2023
@maxulysse maxulysse modified the milestones: 3.2, 3.3 Jun 22, 2023
@FriederikeHanssen FriederikeHanssen added the good first issue Good for newcomers label Aug 15, 2023
@maxulysse maxulysse modified the milestones: 3.3, 3.4, 3.5 Feb 8, 2024
@FriederikeHanssen FriederikeHanssen self-assigned this Oct 29, 2024
@FriederikeHanssen FriederikeHanssen modified the milestones: 3.5, 3.6 Mar 24, 2025
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