DepLink: an R Shiny app to systematically link genetic and pharmacologic dependencies of cancer
Year: 2023
Type: article
Abstract: 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. Here we present DepLink, an R Shiny 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 perturbation expression signatures. The datasets are systematically connected by four complementary modules tailored for different query scenarios. In summary, DepLink enables easy navigation, visualization, and linkage of rapidly evolving cancer dependency maps.
Source: Bioinformatics Advances
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,472
Funders: Cancer Prevention and Research Institute of Texas, University of Pittsburgh, Georgia Clinical and Translational Science Alliance, National Institutes of Health, Center for Research Computing, University of Pittsburgh, National Cancer Institute, National Institute of Diabetes and Digestive and Kidney Diseases, National Center for Research Resources, National Center for Advancing Translational Sciences
Awards: G1114781936, Mays Cancer Center at UT Health SA, G156786057, G2126012127, Recruitment of First-Time, Tenure-Track Faculty Members, G284113647, G436035484, G4535493433, Predicting Drug Response from Genomic Data Using Deep Learning Methods, G6295543716, G6966134840, G741073515, G7657180965, UTHSCSA Cancer Genome Sequencing and Computation Core, G9000010196, G9000019890, G9000031852, G9000068631, G9000217503, G9000274618
OpenAlex ID: W4380867103