Open berguner opened 2 years ago
Hi! You can always achieve this by setting the parrameter --skip_tools baserecalibrator
. I will add some docs on this.
But wouldn't that make the pipeline skip recalibration for SNV/indel calling also? I usually run the pipeline with --tools "mutect2,vep,cnvkit"
.
Yes, currently it is only possible to do one "type" of pre-processing.
I would transfer this to a bigger feature requests:
For scenarios such as above, it would be nice to allow different types of preprocessing. This would require tool based preprocessing steps, that ideally would still be customizable.
Such as:
md+ bqsr + haplotypecaller no md + bqsr + deepvariant md + no bqsr + cnvkit
(examples are completely made up)
This would llikely entail quite a massive change in how we manage data flow at the moment
Other current options as a work around:
Utilize the --step
functions to run the one tool that needs different preprocessing on the respective csv
file that is available in results/csv
to avoid duplicate mapping for example and save time & resources
Description of feature
Hi, It seems like the CNVkit workflow uses
cram_recalibrated
files as input here: https://github.com/nf-core/sarek/blob/bcd7bf9cb98cddec27bb54fb47ee122c09388c02/subworkflows/nf-core/variantcalling/cnvkit/main.nf#L8-L12. As far as I remember, recalibrated files of WES or panel samples don't contain off-target reads because base recalibration is applied over the intervals only. It would be better using CRAM files containing all the reads (cram_markduplicates
?) for CNVkit analysis for utilizing off-target reads. This is especially important for custom panels where there are fewer target regions compared to WES.