MAVE-NN: learning genotype-phenotype maps from multiplex assays of variant effect.
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ABSTRACT:
SUBMITTER: Tareen A
PROVIDER: S-EPMC9011994 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
Publications
MAVE-NN: learning genotype-phenotype maps from multiplex assays of variant effect.
Tareen Ammar A Kooshkbaghi Mahdi M Posfai Anna A Ireland William T WT McCandlish David M DM Kinney Justin B JB
Genome biology 20220415 1
Multiplex assays of variant effect (MAVEs) are a family of methods that includes deep mutational scanning experiments on proteins and massively parallel reporter assays on gene regulatory sequences. Despite their increasing popularity, a general strategy for inferring quantitative models of genotype-phenotype maps from MAVE data is lacking. Here we introduce MAVE-NN, a neural-network-based Python package that implements a broadly applicable information-theoretic framework for learning genotype-p ...[more]
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