Does this skill require local data files or API access?

The skill supports both. It provides patterns for querying the DepMap Portal API for quick lookups and optimized Python workflows for analyzing large-scale CSV downloads locally.

What metrics does the skill use to measure gene dependency?

It primarily uses Chronos scores for CRISPR data, where more negative values indicate higher essentiality, and DEMETER2 for RNA interference data.

What is the primary use of the DepMap skill?

It is used to identify gene dependencies and drug sensitivities in cancer cell lines, helping researchers validate therapeutic targets and find potential biomarkers.

Can I use this for synthetic lethality screening?

Yes, the skill includes specific workflows to identify genes that are selectively essential in cell lines with specific mutations or deletions.

DepMap Cancer Genomics

Name: DepMap Cancer Genomics
Author: lingxling

bylingxling

•

Data Science & ML

Analyzes cancer cell line dependencies and drug sensitivities using the Broad Institute's Cancer Dependency Map data.

The DepMap skill enables researchers and developers to programmatically access and analyze the Cancer Dependency Map (DepMap) dataset, facilitating the identification of cancer-specific vulnerabilities and synthetic lethal interactions. It provides structured workflows for querying CRISPR Chronos dependency scores, validating oncology drug targets, and performing biomarker analysis across hundreds of cancer cell lines. By integrating API access patterns and local data processing logic, this skill streamlines the process of discovering therapeutic targets and predicting cellular responses to gene knockouts or chemical compounds.

Key Features

0146 GitHub stars

02Query CRISPR Chronos and RNAi dependency scores across cancer cell lines

03Identify selective dependencies and cancer-specific therapeutic targets

04Perform biomarker analysis correlating gene mutations with dependency

05Access PRISM drug sensitivity data and compound screening results

06Execute co-essentiality analysis to find functionally related gene pairs

Use Cases

01Identifying synthetic lethal partners for tumor suppressor gene deletions like BRCA1

02Validating whether a specific gene is essential for survival in KRAS-mutant lung cancer lines

03Discovering genomic biomarkers that predict sensitivity to specific oncology compounds

Key Features

0146 GitHub stars

02Query CRISPR Chronos and RNAi dependency scores across cancer cell lines

03Identify selective dependencies and cancer-specific therapeutic targets

04Perform biomarker analysis correlating gene mutations with dependency

05Access PRISM drug sensitivity data and compound screening results

06Execute co-essentiality analysis to find functionally related gene pairs

Use Cases

01Identifying synthetic lethal partners for tumor suppressor gene deletions like BRCA1

02Validating whether a specific gene is essential for survival in KRAS-mutant lung cancer lines

03Discovering genomic biomarkers that predict sensitivity to specific oncology compounds