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Systematic benchmarking of omics computational tools

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 practi...

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Detalles Bibliográficos
Autores principales: Mangul, Serghei, Martin, Lana S., Hill, Brian L., Lam, Angela Ka-Mei, Distler, Margaret G., Zelikovsky, Alex, Eskin, Eleazar, Flint, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437167/
https://www.ncbi.nlm.nih.gov/pubmed/30918265
http://dx.doi.org/10.1038/s41467-019-09406-4
Descripción
Sumario: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.