DepLink: An R Shiny app to systematically link genetic and pharmacologic dependencies of cancer

Tapsya Nayak, Li Ju Wang, Michael Ning, Gabriela Rubannelsonkumar, Eric Jin, Siyuan Zheng, Peter J. Houghton, Yufei Huang, Yu Chiao Chiu, Yidong Chen

Research output: Contribution to journalArticlepeer-review


Motivation: Large-scale genetic and pharmacologic dependency maps are generated to reveal genetic vulnerabilities and drug sensitivities of cancer. However, user-friendly software is needed to systematically link such maps. Results: Here, we present DepLink, a web server to identify genetic and pharmacologic perturbations that induce similar effects on cell viability or molecular changes. DepLink integrates heterogeneous datasets of genome-wide CRISPR loss-of-function screens, high-throughput pharmacologic screens and gene expression signatures of perturbations. The datasets are systematically connected by four complementary modules tailored for different query scenarios. It allows users to search for potential inhibitors that target a gene (Module 1) or multiple genes (Module 2), mechanisms of action of a known drug (Module 3) and drugs with similar biochemical features to an investigational compound (Module 4). We performed a validation analysis to confirm the capability of our tool to link the effects of drug treatments to knockouts of the drug's annotated target genes. By querying with a demonstrating example of CDK6, the tool identified well-studied inhibitor drugs, novel synergistic gene and drug partners and insights into an investigational drug. In summary, DepLink enables easy navigation, visualization and linkage of rapidly evolving cancer dependency maps.

Original languageEnglish (US)
Article numbervbad076
JournalBioinformatics Advances
Issue number1
StatePublished - 2023

ASJC Scopus subject areas

  • Structural Biology
  • Molecular Biology
  • Genetics
  • Computer Science Applications


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