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. 2017 Nov 1;33(21):3489-3491.
doi: 10.1093/bioinformatics/btx415. Epub 2017 Jun 26.

The KSEA App: a web-based tool for kinase activity inference from quantitative phosphoproteomics

Danica D Wiredja  1 , Mehmet Koyutürk  2 , Mark R Chance  1
Affiliations

The KSEA App: a web-based tool for kinase activity inference from quantitative phosphoproteomics

Danica D Wiredja et al. Bioinformatics. .

Abstract

Summary: Computational characterization of differential kinase activity from phosphoproteomics datasets is critical for correctly inferring cellular circuitry and how signaling cascades are altered in drug treatment and/or disease. Kinase-Substrate Enrichment Analysis (KSEA) offers a powerful approach to estimating changes in a kinase's activity based on the collective phosphorylation changes of its identified substrates. However, KSEA has been limited to programmers who are able to implement the algorithms. Thus, to make it accessible to the larger scientific community, we present a web-based application of this method: the KSEA App. Overall, we expect that this tool will offer a quick and user-friendly way of generating kinase activity estimates from high-throughput phosphoproteomics datasets.

Availability and implementation: the KSEA App is a free online tool: casecpb.shinyapps.io/ksea/. The source code is on GitHub: github.com/casecpb/KSEA/. The application is also available as the R package "KSEAapp" on CRAN: CRAN.R-project.org/package=KSEAapp/.

Contact: mark.chance@case.edu.

Supplementary information: Supplementary data are available at Bioinformatics online.

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