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Essential guidelines for computational method benchmarking.

ABSTRACT: In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology.

SUBMITTER: Weber LM

PROVIDER: S-EPMC6584985 | biostudies-other | 2019 Jun

REPOSITORIES: biostudies-other

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Essential guidelines for computational method benchmarking.

Weber Lukas M LM Saelens Wouter W Cannoodt Robrecht R Soneson Charlotte C Hapfelmeier Alexander A Gardner Paul P PP Boulesteix Anne-Laure AL Saeys Yvan Y Robinson Mark D MD

Genome biology 20190620 1

In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide ...[more]

PMID: 31221194

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