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expand Clinical biomarkers #202
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Hi @user-tq (cc @lhogstrom), Thanks for reaching out! I am glad you find the project useful, and appreciate your time looking into the biomarker matching part. Basically, you are touching upon a very challenging part with respect to variant interpretation, that is to match existing biomarkers against a set of variants coming from a tumor/patient. There are two essential sides to this challenge:
As i think you have realized, there are numerous entries in CIViC that comes at a fairly coarse-grained resolution (e.g. Regarding your examples:
Thanks again for your interest in these matters! kind regards, |
thanks,I learned a lot again |
Hey @user-tq, Was looking a bit more into MET exon 14 skipping mutations. It seems that variants (SNVs) located at the canonical splice site on one end (of the adjacent intron) are attributed to exon skipping (NM_000245.2:c.3028+1G and NM_000245.2:c.3028+2T): https://brb.nci.nih.gov/cgi-bin/splicing/splicing_main.cgi This knowledge should be curated and shown in PCGR. Thanks for input! best, |
This is an amazing project. I learned a lot from it.
I noticed this
It seems to lose some info.
for instance
These cannot be converted to genomic variants through TransVar.But they should not be discarded.
I tried to build a complete local database containing the relationship between mutations and drugs. The result annotated in vep/annovar is used as the query input.
When querying the civic database, I found that there are so many variants that it seems impossible to establish a unified set of rules.
Besides, I don't know what the result of VEP/annovar annotation is, so I can't build a dictionary to convert it into the input field of the database.
Do you have any ideas and suggestions about this?
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