TY - JOUR
T1 - DepLink
T2 - An R Shiny app to systematically link genetic and pharmacologic dependencies of cancer
AU - Nayak, Tapsya
AU - Wang, Li Ju
AU - Ning, Michael
AU - Rubannelsonkumar, Gabriela
AU - Jin, Eric
AU - Zheng, Siyuan
AU - Houghton, Peter J.
AU - Huang, Yufei
AU - Chiu, Yu Chiao
AU - Chen, Yidong
N1 - Funding Information:
This work was supported partially by the National Institutes of Health [R00CA248944 to Y.-C.C., CTSA 1UL1RR025767 to Y.C., NCI P30CA047904 to UPMC Hillman Cancer Center, NCI Cancer Center Shared Resources P30CA54174 to Y.C., NIDDK P30DK120531 to Pittsburgh Liver Research Center]; Cancer Prevention and Research Institute of Texas [RP220662 to Y.C., RP190346 to Y.C. and Y.H., RR170055 to S.Z.]; and the Fund for Innovation in Cancer Informatics to Y.-C.C. and Y.C. This research was also supported in part by the University of Pittsburgh Center for Research Computing. The funding sources had no role in the design of the study; collection, analysis and interpretation of data; or in writing the manuscript.
Publisher Copyright:
© 2023 The Author(s). Published by Oxford University Press.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
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U2 - 10.1093/bioadv/vbad076
DO - 10.1093/bioadv/vbad076
M3 - Article
C2 - 37359725
AN - SCOPUS:85164326994
SN - 2635-0041
VL - 3
JO - Bioinformatics Advances
JF - Bioinformatics Advances
IS - 1
M1 - vbad076
ER -