Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects

• DOI: 10.1186/s13059-021-02540-7
• Publication Date: 2021-12-20T08:04:56Z
• Authors: Joshua M. Dempster; Isabella Boyle; Francisca Vazquez; David E. Root; Jesse S. Boehm; William C. Hahn; Aviad Tsherniak; James M. McFarland
• Keywords: 0303 health sciences; Genome; QH301-705.5; Population Dynamics; Method; Computational Biology; QH426-470; Gene Knockout Techniques; 03 medical and health sciences; Neoplasms; Genetics; Biomarkers, Tumor; Humans; Clustered Regularly Interspaced Short Palindromic Repeats; Biology (General); CRISPR-Cas Systems; Algorithms; Gene Library

AbstractCRISPR loss of function screens are powerful tools to interrogate biology but exhibit a number of biases and artifacts that can confound the results. Here, we introduce Chronos, an algorithm for inferring gene knockout fitness effects based on an explicit model of cell proliferation dynamics after CRISPR gene knockout. We test Chronos on two pan-cancer CRISPR datasets and one longitudinal CRISPR screen. Chronos generally outperforms competitors in separation of controls and strength of biomarker associations, particularly when longitudinal data is available. Additionally, Chronos exhibits the lowest copy number and screen quality bias of evaluated methods. Chronos is available at https://github.com/broadinstitute/chronos.