Open MattWellie opened 6 months ago
Hi Matt,
Cheers, Chiara
In general, there aren't a huge number of 'real' looking STR expansion calls in these reports. If you can mostly filter by what is rare in our callset then I don't think you'll end up with too much noise if using the pathogenic cut-offs (or even just outliers) in those databases. Relying too heavily on MOI may not be as helpful especially for large STRs that are difficult to accurately detect in short read data.
In general, there aren't a huge number of 'real' looking STR expansion calls in these reports. If you can mostly filter by what is rare in our callset then I don't think you'll end up with too much noise if using the pathogenic cut-offs (or even just outliers) in those databases.
+1 on this. Stripy reports very few variants and it already has good logic in place for flagging potentially pathogenic expansions that need review. The only issue seems to be ~2 loci that regularly turn up artefact calls. I have chatted with Andre about how to tune these better, but for the moment my feeling is just to hard blacklist these loci.
All we need to do is pull the flaged variants out of the json and pass them directly as a category. The biggest pain is probably going to be transforming them into a pseudo variant call we can inject in to seqr so we can represent them there. Stand alone reports will be fine, but it will just take some time to work through in seqr.
STRs as a new variant type to include in analysis.
We are making use of Small variants and SVs (see #372... 😞), but CPG already runs STRipy reports on all samples. We can use that as a source of input data, pending any teething problems with incorporating STR logic in the MOI algorithms...