Systematic benchmarking of omics computational tools

Serghei Mangul; Lana S. Martin; Brian L. Hill; Angela Ka-Mei Lam; Margaret G. Distler; Alex Zelikovsky; Eleazar Eskin; Jonathan Flint

doi:10.1038/s41467-019-09406-4

Nature Communications (Mar 2019)

Systematic benchmarking of omics computational tools

Serghei Mangul,
Lana S. Martin,
Brian L. Hill,
Angela Ka-Mei Lam,
Margaret G. Distler,
Alex Zelikovsky,
Eleazar Eskin,
Jonathan Flint

Affiliations

Serghei Mangul: Department of Computer Science, University of California Los Angeles
Lana S. Martin: Institute for Quantitative and Computational Biosciences, University of California Los Angeles
Brian L. Hill: Department of Computer Science, University of California Los Angeles
Angela Ka-Mei Lam: Department of Computer Science, University of California Los Angeles
Margaret G. Distler: Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles
Alex Zelikovsky: Department of Computer Science, Georgia State University
Eleazar Eskin: Department of Computer Science, University of California Los Angeles
Jonathan Flint: Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles

DOI: https://doi.org/10.1038/s41467-019-09406-4
Journal volume & issue: Vol. 10, no. 1
pp. 1 – 11

Abstract

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Benchmarking studies are important for comprehensively understanding and evaluating different computational omics methods. Here, the authors review practices from 25 recent studies and propose principles to improve the quality of benchmarking studies.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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