depmap

To validate oncology targets with DepMap data, query gene essentiality across specific cancer cell lines by checking Chronos dependency scores. This confirms whether your target gene is consistently essential in the relevant cancer lineages.

You can discover predictive biomarkers by correlating gene dependencies with molecular features in cancer cell lines. This process identifies molecular characteristics that predict sensitivity to specific gene disruptions or drug treatments.

Synthetic lethality analysis finds gene pairs showing cancer-selective dependencies by querying DepMap data for co-essential genes. This identifies combination therapy strategies where the loss of one gene creates a vulnerability dependent on another.

The DepMap dataset includes drug sensitivities for cancer cell lines alongside Chronos-based CRISPR dependency scores and cell line metadata. This supports end-to-end analysis workflows for target validation and biomarker discovery.

Downloadable datasets are available to enable end-to-end offline cancer dependency analysis workflows. These include cell line metadata, Chronos dependency scores, and molecular features for comprehensive target and biomarker research.