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 and Jonathan Flint
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Serghei Mangul: University of California Los Angeles
Lana S. Martin: University of California Los Angeles
Brian L. Hill: University of California Los Angeles
Angela Ka-Mei Lam: University of California Los Angeles
Margaret G. Distler: University of California Los Angeles
Alex Zelikovsky: Georgia State University
Eleazar Eskin: University of California Los Angeles
Jonathan Flint: University of California Los Angeles

Nature Communications, 2019, vol. 10, issue 1, 1-11

Abstract: Abstract Computational omics methods packaged as software have become essential to modern biological research. The increasing dependence of scientists on these powerful software tools creates a need for systematic assessment of these methods, known as benchmarking. Adopting a standardized benchmarking practice could help researchers who use omics data to better leverage recent technological innovations. Our review summarizes benchmarking practices from 25 recent studies and discusses the challenges, advantages, and limitations of benchmarking across various domains of biology. We also propose principles that can make computational biology benchmarking studies more sustainable and reproducible, ultimately increasing the transparency of biomedical data and results.

Date: 2019
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DOI: 10.1038/s41467-019-09406-4

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