Processed data (CRISPR vs. RNAi)

The referenced software pipeline creates and stores this set of intermediate files which are then used to generate figures and supplemental tables for Krill-Burger et al., “Partial inhibition improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal”. While many of these files are primarily deposited to speedup code runtime by allowing users to load precomputed intermediary files, there are a few useful result tables. Most notably, these results include pan-dependency scores and probability of dependency (Bayesian inference of gene effects used for binary hit calling) for each genetic perturbation dataset as well as predictive models (ensemble of random forests) for each gene effect profile using multi-omics datasets as predictive features. File types are comma separated text files (csv) or R data objects (rds). See the ReadMe.pdf for detailed file descriptions.