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Latest Release DepMap Public 18Q4 | November 2018


The DepMap Public 18Q4 release includes CRISPR screen and omics datasets expanded to include new cell lines. The Avana CRISPR screen dataset is expanded to include 517 cell lines. Mutation, indel, copy number and gene expression data are also expanded to include new lines in Avana dataset. As our screening efforts continue, we will be releasing additional cancer dependency data on a quarterly basis.

The CRISPR screen uses the Avana CRISPR-Cas9 genome-scale knockout library, and descriptions of the experimental methods and the CERES algorithm are published in here. The previously published line ACH-000005 has been dropped for slipping over the edge of QC failure.

Copy number and mutation data for some cell lines were based on Sanger Institute whole exome sequencing data (COSMIC: http://cancer.sanger.ac.uk/cell_lines, EGA accession number: EGAD00001001039) reprocessed using CCLE pipelines.

For 18Q4, we have added the Variant_annotation column to depmap_18Q4_mutation_calls.csv. This groups mutations according to the Variant_Classication column, and corresponds to the coloring of mutations in the portal. See here for details.

Cellular Models

Expression

Public 18Q4

CCLE RNAseq gene expression data (log2(TPM+1)). The portal shows expression data for only protein coding genes; this download is the full dataset.

Genes 56202
Cell Lines 1156
Primary Diseases 32
Lineages 32

Cellular Models

Mutation

Public 18Q4

Merged mutation calls (coding region, germline filtered)

Genes 18701
Cell Lines 1596
Primary Diseases 37
Lineages 33

Cellular Models

Copy Number

Public 18Q4

DepMap WES CN Data

Genes 23299
Cell Lines 1098
Primary Diseases 32
Lineages 30

Cellular Models

Cell Line Metadata

Metadata about cell lines in the 18Q4 release, including mapping between DepMap ID and CCLE names

Genes 0
Cell Lines 1671
Primary Diseases 38
Lineages 33

Genetic Dependency

CRISPR

(Avana) Public 18Q4

CERES

CERES inferred gene effect matrix

Genes 17634
Cell Lines 517
Primary Diseases 25
Lineages 27

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Genetic Dependency

Combined RNAi

(Broad, Novartis, Marcotte)
Genes 17212
Cell Lines 712
Primary Diseases 54
Lineages 31

Cellular Models

Protein levels

CCLE Reverse Phase Protein Array (RPPA) data

Genes 214
Cell Lines 899
Primary Diseases 59
Lineages 28

Please cite the following publications when using these datasets

For CRISPR datasets:

Broad Institute Cancer Dependency Map; Cancer Data Science (2018): Cancer Dependency Map, CRISPR Avana dataset 18Q4 (Avana_public_18Q4). figshare. Fileset. doi:10.6084/m9.figshare.7270880.v1

Robin M. Meyers, Jordan G. Bryan, James M. McFarland, Barbara A. Weir, ... David E. Root, William C. Hahn, Aviad Tsherniak. Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells. Nature Genetics 2017 October 49:1779–1784. doi:10.1038/ng.3984

For omics datasets:

Cancer Cell Line Encyclopedia Consortium, and Genomics of Drug Sensitivity in Cancer Consortium. 2015. Pharmacogenomic Agreement between Two Cancer Cell Line Data Sets. Nature 528 (7580):84–87. https://doi.org/10.1038/nature15736.

Jordi Barretina, Giordano Caponigro, Nicolas Stransky, Kavitha Venkatesan, William R. Sellers, Robert Schlegel, Levi A. Garraway, et. al. 2012. The Cancer Cell Line Encyclopedia Enables Predictive Modelling of Anticancer Drug Sensitivity. Nature 483 (7391):603–7. https://doi.org/10.1038/nature11003.

For the RNAi dataset:

James M. McFarland, Zandra V. Ho, Guillaume Kugener, Joshua M. Dempster, Phillip G. Montgomery, Jordan G. Bryan, John M. Krill-Burger, Thomas M. Green, Francisca Vazquez, Jesse S. Boehm, Todd R. Golub, William C. Hahn, David E. Root, Aviad Tsherniak. (2018). Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration. Nature Communications 9, 1. https://doi.org/10.1038/s41467-018-06916-5


This data was generated in part from funding from:

This project is partially funded by CTD2, the Achilles consortium, and The Carlos Slim Foundation in Mexico through the Slim Initiative for Genomic Medicine.