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posted on 2020-04-09, 17:06 authored by Cancer Data ScienceCancer Data Science
Cancer cell line genetic dependencies estimated using the DEMETER2 model. DEMETER2 is applied to three large-scale RNAi screening datasets: the Broad Institute Project Achilles, Novartis Project DRIVE, and the Marcotte et al. breast cell line dataset. The model is also applied to generate a combined dataset of gene dependencies covering a total of 712 unique cancer cell lines. For more information visit https://depmap.org/R2-D2/.

Visit the Cancer Dependency Map portal at https://depmap.org to explore related datasets. Email questions to depmap@broadinstitute.org

This dataset includes gene dependencies estimated using the DEMETER2 model, the raw input datasets used to fit the models, as well as associated metadata. See Readme file for more details about the dataset contents and version history.

Version history: (see README for more details)
v1: Initial data release

- Removed small number of non-human genes (e.g. GFP, RFP) from shRNA-to-gene mapping
- Updated cell line names to be consistent with DepMap names, according to the following map (old -> new):

v3: Added estimated seed effect matrices

v4: Added RNAseq and mutation data files used in analysis for manuscript

v5: Fixed minor bug with Marcotte LFC data that caused hairpins targeting multiple genes to appear multiple times in the LFC matrix. This created bias in the seed effect estimates for those hairpins, causing very minor differences to the resulting model parameters.

v6: Added tables with shRNA quality metrics for Achilles and DRIVE data