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Add cancer_gene flag to get_gene_information #107
Add cancer_gene flag to get_gene_information #107
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graphkb/genes.py
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@@ -444,6 +444,10 @@ def get_gene_information( | |||
gene_flags["oncogene"] = convert_to_rid_set(get_oncokb_oncogenes(graphkb_conn)) | |||
logger.info("fetching tumour supressors list") | |||
gene_flags["tumourSuppressor"] = convert_to_rid_set(get_oncokb_tumour_supressors(graphkb_conn)) | |||
logger.info("fetching cancer_gene list") | |||
gene_flags["cancer_gene"] = convert_to_rid_set(get_cancer_genes(graphkb_conn)) |
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Hi @mathieulemieux - did you check that IPR is already able to accept 'cancer_gene'?
Hi @Nithriel, @mathieulemieux
Is there a reason why 'cancer_gene' is not camel case like all the other gene flags? eg. (cancerRelated, tumourSuppressor)
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did you check that IPR is already able to accept 'cancer_gene'?
Work needed to be done on both side, gkb and ipr, and I don't thing it matters which one first, as long as we make sure it's done on both sides before release. @Nithriel should tell us when the work on her side is done.
Is there a reason why 'cancer_gene' is not camel case like all the other gene flags?
I thought we agreed on that before. I can change it to camel case if not too late from the ipr side. @Nithriel , what is the exact flag you're using on your side?
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cancer_gene changed for cancerGene.
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## develop #107 +/- ##
===========================================
+ Coverage 90.33% 90.35% +0.02%
===========================================
Files 8 8
Lines 838 840 +2
===========================================
+ Hits 757 759 +2
Misses 81 81
Flags with carried forward coverage won't be shown. Click here to find out more. ☔ View full report in Codecov by Sentry. |
@@ -23,7 +23,7 @@ | |||
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CANONICAL_ONCOGENES = ["kras", "nras", "alk"] | |||
CANONICAL_TS = ["cdkn2a", "tp53"] | |||
CANONICAL_CG = ["ercc1", "fanci", "h2bc4", "h2bc17", "acvr1b"] |
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just curious, were these genes not good tests?
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I first chose these gene randomly among the 500+ I had on hand, then I replaced them with gene 'alb' that I knew I had a related Statement in GKB. The list is here to be fill with more 'canonical' ones once we have some specific use cases we want to test for. I didn't wanted to make it looks as these genes were 'special', so I removed them.
See https://www.bcgsc.ca/jira/browse/KBDEV-1129