Clustering-Based Methods for Clinical Risk Prediction of Rare Missense Variants
A long-standing goal in clinical genomics is to map individual genetic variants to clinical outcomes. Typically, variants which lead to loss of function (e.g. nonsense or stop-codon inducing variants, frameshifts, or deletions) are more easily classified as pathogenic in an established disease gene....
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Format: | Thesis |
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Massachusetts Institute of Technology
2022
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Online Access: | https://hdl.handle.net/1721.1/139502 |