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Orientation Model (F1R2/F2R1) runs on data from single-end tech
I am currently working on data from a tiny gene panel (~29 kb; target enrichment by amplicons) with deep coverage in most of the samples (mean coverage well above 1000x in most samples). Data is single-end reads.
I followed the recently updated tutorial for somatic variant calling to run Mutect2. Then I realized that it probably does not make any sense to run the
--f1r2-tar-gz option and the subsequent
LearnReadOrientationModel tool on my data, being from single-end-reads technology. However, I was surprised to see that not only the tools did not complain of receiving single-end reads but also produced a
.orientation_priors filled with data, which can be passed to
FilterMutectCalls also without raising any errors. How is this possible?
Please notice that I also posted another question about applying GATK tools to uncommon datasets like the one here described (small panels, single-end, amplicons) about a week ago. It would be great if you could give some orientation about to what extent GATK is applicable to this sort of data, which is being massively produced around the world for targeted sequencing of small regions of interest (typically hotspot panels in cancer).