DiMSum: an error model and pipeline for analyzing deep mutational scanning data and diagnosing common experimental pathologies

DiMSum: an error model and pipeline for analyzing deep mutational scanning data and diagnosing common experimental pathologies

Abstract Deep mutational scanning (DMS) enables multiplexed measurement of the effects of thousands of variants of proteins, RNAs, and regulatory elements. Here, we present a customizable pipeline, DiMSum, that represents an end-to-end solution for obtaining variant fitness and error estimates from...

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Bibliographic Details
Main Authors: Andre J. Faure, Jörn M. Schmiedel, Pablo Baeza-Centurion, Ben Lehner
Format: Article
Language:English
Published: BMC 2020-08-01
Series:Genome Biology
Subjects:
Deep mutational scanning
Bioinformatic pipeline
Statistical model
Variant effect prediction
R package
Bioconda
Online Access:http://link.springer.com/article/10.1186/s13059-020-02091-3

Internet

http://link.springer.com/article/10.1186/s13059-020-02091-3

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