GEMINI: a variational Bayesian approach to identify genetic interactions from combinatorial CRISPR screens

Mahdi Zamanighomi; Sidharth S Jain; Takahiro Ito; Debjani Pal; Timothy P Daley; William R Sellers

doi:10.1186/s13059-019-1745-9

GEMINI: a variational Bayesian approach to identify genetic interactions from combinatorial CRISPR screens

Genome Biol. 2019 Jul 12;20(1):137. doi: 10.1186/s13059-019-1745-9.

Authors

Mahdi Zamanighomi¹, Sidharth S Jain¹, Takahiro Ito¹, Debjani Pal¹, Timothy P Daley^{2

3}, William R Sellers^{4

5

6}

Affiliations

¹ Broad Institute of MIT and Harvard, Cambridge, 02142, USA.
² Department of Statistics, Stanford University, Stanford, 94305, USA.
³ Department of Bioengineering, Stanford University, Stanford, 94305, USA.
⁴ Broad Institute of MIT and Harvard, Cambridge, 02142, USA. wsellers@broadinstitute.org.
⁵ Deparment of Medical Oncology, Dana-Farber Cancer Institute, Boston, 02115, USA. wsellers@broadinstitute.org.
⁶ Department of Medicine, Harvard Medical School, Boston, 02115, USA. wsellers@broadinstitute.org.

Abstract

Systems for CRISPR-based combinatorial perturbation of two or more genes are emerging as powerful tools for uncovering genetic interactions. However, systematic identification of these relationships is complicated by sample, reagent, and biological variability. We develop a variational Bayes approach (GEMINI) that jointly analyzes all samples and reagents to identify genetic interactions in pairwise knockout screens. The improved accuracy and scalability of GEMINI enables the systematic analysis of combinatorial CRISPR knockout screens, regardless of design and dimension. GEMINI is available as an open source R package on GitHub at https://github.com/sellerslab/gemini .

Keywords: CRISPR; Combinatorial; Double knockout; GEMINI; Genetic interactions; Synthetic lethality; Variational inference.

Publication types

Evaluation Study
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Bayes Theorem
Clustered Regularly Interspaced Short Palindromic Repeats*
Epistasis, Genetic
Genetic Techniques*
Software*