A probabilistic graphical model for estimating selection coefficients of nonsynonymous variants from human population sequence data
Abstract Accurately predicting the effect of missense variants is important in discovering disease risk genes and clinical genetic diagnostics. Commonly used computational methods predict pathogenicity, which does not capture the quantitative impact on fitness in humans. We develop a method, MisFit,...
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| Main Authors: | Yige Zhao, Tian Lan, Guojie Zhong, Jake Hagen, Hongbing Pan, Wendy K. Chung, Yufeng Shen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-59937-2 |
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