Victor A. Zhivich

TL;DR: CERES, a computational method to estimate gene-dependency levels from CRISPR–Cas9 essentiality screens while accounting for the copy number–specific effect, is developed and found that CERES decreased false-positive results and estimated sgRNA activity for both this data set and previously published screens performed with different sg RNA libraries.

TL;DR: CERES, a computational method to estimate gene dependency levels from CRISPR-Cas9 essentiality screens while accounting for the copy-number-specific effect, as well as variable sgRNA activity, is developed and applied to sets of screens performed with different sgRNAs and found that it reduces false positive results and provides meaningful estimates of sg RNA activity.

TL;DR: The authors show that the two largest independent CRISPR-Cas9 gene-dependency screens are concordant, paving the way for joint analysis of the data sets.

TL;DR: It is found that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length, which indicates that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings.