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We would skip g2d if there are multiple causal genes for that disease.
We could explore other approaches - e.g. using the Mondo mappings which tell us when an ordo class is subsuming OMIMs, but the g2d cardinality approach is simple and standalone and will leave us in a much better place than we are now
The text was updated successfully, but these errors were encountered:
From @pnrobinson on email
In the Exomiser, HPO website, Monarch Web app, we find the same medical error.
Orphanet associated some diseases with tons of genes
ORPHA:91387Familial thoracic aortic aneurysm and aortic dissection
MFAP5 [8076 ]
FOXE3 [2301 ]
LOX [4015 ]
MYH11 [4629 ]
PRKG1 [5592 ]
TGFB2 [7042 ]
MAT2A [4144 ]
TGFB3 [7043 ]
ACTA2 [59 ]
SMAD3 [4088 ]
TGFBR2 [7048 ]
TGFBR1 [7046 ]
HEY2 [23493 ]
SMAD4 [4089 ]
SMAD2 [4087 ]
THSD4 [79875 ]
ELN [2006 ]
MYLK [4638 ]
FBN1 [2200 ]
@cmungall's comments:
Yes, monarch-kg gets these association from phenol via http://purl.obolibrary.org/obo/hp/hpoa/genes_to_disease.txt
I suggest we modify this code as per Peter's suggestion:
https://github.com/monarch-initiative/phenol/blob/master/phenol-annotations/src/main/java/org/monarchinitiative/phenol/annotations/assoc/OrphaGeneToDiseaseParser.java
We would skip g2d if there are multiple causal genes for that disease.
We could explore other approaches - e.g. using the Mondo mappings which tell us when an ordo class is subsuming OMIMs, but the g2d cardinality approach is simple and standalone and will leave us in a much better place than we are now
The text was updated successfully, but these errors were encountered: