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sarahhunt
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Feb 14, 2025
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Congratulations on your first plugin @ainefairbrother !
I spotted a couple of typos and places where we can make the information we are supplying clearer.
There are also optimisations we can make by changing data structures; let me know if it's useful to talk about these.
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JIRA ticket: ENSVAR-6662
Description
This PR adds the MechPredict plugin, which annotates missense variants with one of predicted gene-level mechanisms:
MechPredict does this by reading in gene-level probabilities predicted by an external model and assigning the most likely mechanism based on empircally-derived cut-offs described in the related manuscript. For example, if gene A has the following probability values: DN = 0.2, GOF = 0.3, LOF = 0.9, then the returned interpretation would be "gene_predicted_as_associated_with_loss_of_function_mechanism".
Notes
MechPredict_pDN: NumericMechPredict_pGOF: NumericMechPredict_pLOF: NumericMechPredict_interpretation: CharacterMechPredict_input.tsvwhich can be generated using instructions in the module's header.Testing
Test with 50 missense variants - should annotate all
Test with 50 intron variants - should annotate none