MaveQuest: a web resource for planning experimental tests of human variant effects

Author:

Kuang Da1234ORCID,Weile Jochen1234,Li Roujia1234,Ouellette Tom W12,Barber Jarry A12,Roth Frederick P1234

Affiliation:

1. Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada

2. Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada

3. Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON M5G 1X5, Canada

4. Department of Computer Science, University of Toronto, Toronto, ON M5T 3A1, Canada

Abstract

Abstract Summary Fully realizing the promise of personalized medicine will require rapid and accurate classification of pathogenic human variation. Multiplexed assays of variant effect (MAVEs) can experimentally test nearly all possible variants in selected gene targets. Planning a MAVE study involves identifying target genes with clinical impact, and identifying scalable functional assays for that target. Here, we describe MaveQuest, a web-based resource enabling systematic variant effect mapping studies by identifying potential functional assays, disease phenotypes and clinical relevance for nearly all human protein-coding genes. Availability and implementation MaveQuest service: https://mavequest.varianteffect.org/. MaveQuest source code: https://github.com/kvnkuang/mavequest-front-end/. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Human Genome Research Institute

National Institutes of Health Center

Canada Excellence Research Chairs Program

Canadian Institutes of Health Foundation

One Brave Idea Foundation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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