The `gene_summary` dataset contains the 22Q1 gene essentiality probabilities for select genes. This dataset can be loaded into the R environment with the `depmap_gene_summary` function.
Format
A data frame with 69746 rows (cell lines) and 7 variables:
- entrez_id
Entrez ID# (e.g. 100316904)
- gene_name
HUGO symbol (e.g. "SAP25")
- dataset
which dataset this probability derives
- dependent_cell_lines
number of dependent cell lines
- cell_lines_with_data
number of cell lines with relevant dependency data
- strongly_selective
Gene knockout is selective (not pan-lethal)
- common_essential
common essential gene dependency
Details
This data represents the `Gene Dependency Profile Summary.csv` file taken from the 22Q1 [Broad Institute](https://depmap.org/portal/api/download/gene_dep_summary) release.
Change log
- 22Q1: Initial dataset
- 22Q2: no change, no further releases are scheduled at this time.
References
Tsherniak, A., Vazquez, F., Montgomery, P. G., Weir, B. A., Kryukov, G., Cowley, G. S., ... & Meyers, R. M. (2017). Defining a cancer dependency map. Cell, 170(3), 564-576.
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.