mutscan-a flexible R package for efficient end-to-end analysis of multiplexed assays of variant effect data

Charlotte Soneson; Alexandra M Bendel; Guillaume Diss; Michael B Stadler

doi:10.1186/s13059-023-02967-0

mutscan-a flexible R package for efficient end-to-end analysis of multiplexed assays of variant effect data

Genome Biol. 2023 Jun 1;24(1):132. doi: 10.1186/s13059-023-02967-0.

Authors

Charlotte Soneson^{1

2}, Alexandra M Bendel³, Guillaume Diss³, Michael B Stadler^{4

5

6}

Affiliations

¹ Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland. charlotte.soneson@fmi.ch.
² SIB Swiss Institute of Bioinformatics, Basel, Switzerland. charlotte.soneson@fmi.ch.
³ Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
⁴ Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland. michael.stadler@fmi.ch.
⁵ SIB Swiss Institute of Bioinformatics, Basel, Switzerland. michael.stadler@fmi.ch.
⁶ University of Basel, Basel, Switzerland. michael.stadler@fmi.ch.

Abstract

Multiplexed assays of variant effect (MAVE) experimentally measure the effect of large numbers of sequence variants by selective enrichment of sequences with desirable properties followed by quantification by sequencing. mutscan is an R package for flexible analysis of such experiments, covering the entire workflow from raw reads up to statistical analysis and visualization. The core components are implemented in C++ for efficiency. Various experimental designs are supported, including single or paired reads with optional unique molecular identifiers. To find variants with changed relative abundance, mutscan employs established statistical models provided in the edgeR and limma packages. mutscan is available from https://github.com/fmicompbio/mutscan .

Keywords: Deep mutational scanning; Multiplexed assays of variant effect; R package.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

High-Throughput Nucleotide Sequencing*
Software*
Workflow