Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens

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Authors: Maximilian Billmann, Michael Costanzo, Mahfuzur Rahman, Katherine Chan, Amy HY Tong, Herny N Ward, Arshia Zernab Hassan, Xiang Zhang, Kevin R Brown, Thomas Rohde, Angela H Shaw, Catherine Ross
+10 more Jolanda S. van Leeuwen, Michael Aregger, Keith Lawson, Barbara Mair, Patricia Mero, Matej Ušaj, Brenda Andrews, Charles M. Boone, Jason Moffat, Chad L. Myers
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Abstract

The documented code (qGI_scoring.Rmd) supports the manuscript titled "Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens". It generates quantitative genetic interaction (qGI) scores from raw gRNA read counts (provided in a separate Zenodo data repository). This code illustrates the different data processing steps and visualizes aspects of the data where this supports a careful execution of the normalization steps. The code for additional analyses, for instance for re-scoring the data without a normalization step to judge the effect of this given normalization, is not explicitly provided here, but can be synthesized from the code. This documented code sources the qGI_functions.R source code. The scores generated from this code are also described in the manuscript titled "A global genetic interaction map of a human cell reveals conserved principles of genetic networks"

Fields of Study & Subjects

CRISPR and Genetic Engineering Bioinformatics and Genomic Networks Gene Regulatory Network Analysis

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 January 2026
Document type
Book