Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells

CERES is a new computational method to estimate gene-dependency levels from CRISPR–Cas9 essentiality screens while accounting for copy number effects and variable sgRNA activity. Applying CERES to new genome-scale CRISPR–Cas9 essentiality screen data from 342 cancer cell lines and other published data sets shows that CERES decreases false-positive results and provides consistent estimates of sgRNA activity.