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DepMap_18Q4_data.rds (1.49 GB)

DepMap Datasets for WRN manuscript

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posted on 2019-02-13, 14:57 authored by Cancer Data ScienceCancer Data Science
Cancer Dependency Map (DepMap) data used for analyses in the manuscript "WRN Helicase is a Synthetic Lethal Target in Microsatellite Unstable Cancers" by Chan and Shibue et al. is packaged into an rds file.

This rds file contains a list of data matrices. All but one of these matrices ("MUT") have cell lines as rows and genes as columns (gene names are mapped to hgnc symbols).

This analysis uses the 18Q4 DepMap release. The latest Broad Institute DepMap data can be accessed at https://depmap.org.

Associated code for analysis is available at https://github.com/cancerdatasci/WRN_manuscript, and code and other materials can be accessed from https://depmap.org/WRN/

The rds file contains the following datasets:
-DRIVE: Gene dependency scores from the Novartis DRIVE RNAi screen[1] processed using the DEMETER2 algorithm[2].

-CRISPR: Gene dependency scores from the Achilles CRISPR screen processed using the CERES algorithm[3].

-GE: Gene expression data (log2(TPM), protein coding genes only) [4].

-CN: Log2 relative copy number [4].

-MUT_HOT: Binary matrix indicating which cell lines have hotspot missense mutations in each gene

-MUT_DAM: Binary matrix indicating which cell lines have damaging mutations in each gene

-MUT_OTHER: Binary matrix indicating which cell lines have other non-silent mutations in each gene

-MUT: Dataframe containing all mutation calls from the DepMap 18Q4 release [4]

-RPPA: CCLE protein abundance data using reverse-phase protein array [4].

References
[1] McDonald, E.R., et al., Project DRIVE: A Compendium of Cancer Dependencies and Synthetic Lethal Relationships Uncovered by Large-Scale, Deep RNAi Screening. Cell. 170, 577-592 (2017).

[2] McFarland, J.M., et al., Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration. Nat. Commun. 9, 4610 (2018).

[3] Meyers, R.M., et al., Computational correction of copy number effect improves specificity of CRISPR–Cas9 essentiality screens in cancer cells. Nat. Genet. 49, 1779 (2017).

[4] Cancer Cell Line Encyclopedia Consortium, and Genomics of Drug Sensitivity in Cancer Consortium. Pharmacogenomic Agreement between Two Cancer Cell Line Data Sets. Nature. 528, 84–87 (2015).

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