Computational correction of copy-number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells
Robin M. Meyers, Jordan G. Bryan, et al. Nature Genetics 2017
Summary
The CRISPR–Cas9 system has enabled precise genome-scale identification of genes essential for proliferation and survival of cancer cells. However, Cas9-mediated DNA cleavage produces a gene-independent antiproliferative effect that confounds such measurement of genetic dependency. We developed CERES to estimate gene-dependency levels from CRISPR-Cas9 essentiality screens while accounting for this effect.
In our efforts to define a cancer dependency map, we performed genome-scale CRISPR-Cas9 essentiality screens across 342 cancer cell lines and applied CERES to these data. In this work, we further demonstrate the utility of this collection of screens, after CERES correction, for identifying cancer-type-specific vulnerabilities.
See the preprint on bioRxiv
Datasets
Avana
The latest collection of CRISPR screening data from the Dependency Map using the Avana library.
Manuscript files
Link to data used in CERES manuscript.
Includes results of running CERES on 342 cancer cell lines screened with the Avana sgRNA library, 33 cancer cell lines screened with the GeCKOv2 sgRNA library published in Aguirre et al. 2016, and 14 AML cancer cell lines published in Wang et al. 2017.
CERES demo
Download pre-packaged Gecko + Wang2017 data files to quickly run the example script from the CERES GitHub repo.
You may also download the necessary bowtie indices here. Note that the index files are large and will take some time to download.
Software
CERES for R
Clone or download the R package GitHub repository to run CERES on CRISPR-Cas9 essentiality screening data
Scripts for generating figures
Clone or download to generate figures from the manuscript
