MAUDE: inferring expression changes in sorting-based CRISPR screens.

Genome Biol
Authors
Keywords
Abstract

Improved methods are needed to model CRISPR screen data for interrogation of genetic elements that alter reporter gene expression readout. We create MAUDE (Mean Alterations Using Discrete Expression) for quantifying the impact of guide RNAs on a target gene's expression in a pooled, sorting-based expression screen. MAUDE quantifies guide-level effects by modeling the distribution of cells across sorting expression bins. It then combines guides to estimate the statistical significance and effect size of targeted genetic elements. We demonstrate that MAUDE outperforms previous approaches and provide experimental design guidelines to best leverage MAUDE, which is available on https://github.com/Carldeboer/MAUDE.

Year of Publication
2020
Journal
Genome Biol
Volume
21
Issue
1
Pages
134
Date Published
2020 06 03
ISSN
1474-760X
DOI
10.1186/s13059-020-02046-8
PubMed ID
32493396
PubMed Central ID
PMC7268349
Links
Grant list
K99-HG009920-01 / HG / NHGRI NIH HHS / United States
5 F32 AI129249 / NH / NIH HHS / United States
RM1HG006193 / NH / NIH HHS / United States
R01HG008131-01 / NH / NIH HHS / United States
CIHR / Canada
HHMI / Howard Hughes Medical Institute / United States