MAUDE: inferring expression changes in sorting-based CRISPR screens.
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 06 03
|PubMed Central ID||
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