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Essential guidelines for computational method benchmarking

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 determin...

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Autores principales: Weber, Lukas M., Saelens, Wouter, Cannoodt, Robrecht, Soneson, Charlotte, Hapfelmeier, Alexander, Gardner, Paul P., Boulesteix, Anne-Laure, Saeys, Yvan, Robinson, Mark D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6584985/
https://www.ncbi.nlm.nih.gov/pubmed/31221194
http://dx.doi.org/10.1186/s13059-019-1738-8
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author Weber, Lukas M.
Saelens, Wouter
Cannoodt, Robrecht
Soneson, Charlotte
Hapfelmeier, Alexander
Gardner, Paul P.
Boulesteix, Anne-Laure
Saeys, Yvan
Robinson, Mark D.
author_facet Weber, Lukas M.
Saelens, Wouter
Cannoodt, Robrecht
Soneson, Charlotte
Hapfelmeier, Alexander
Gardner, Paul P.
Boulesteix, Anne-Laure
Saeys, Yvan
Robinson, Mark D.
author_sort Weber, Lukas M.
collection PubMed
description 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.
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spelling pubmed-65849852019-06-27 Essential guidelines for computational method benchmarking Weber, Lukas M. Saelens, Wouter Cannoodt, Robrecht Soneson, Charlotte Hapfelmeier, Alexander Gardner, Paul P. Boulesteix, Anne-Laure Saeys, Yvan Robinson, Mark D. Genome Biol Review 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. BioMed Central 2019-06-20 /pmc/articles/PMC6584985/ /pubmed/31221194 http://dx.doi.org/10.1186/s13059-019-1738-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Review
Weber, Lukas M.
Saelens, Wouter
Cannoodt, Robrecht
Soneson, Charlotte
Hapfelmeier, Alexander
Gardner, Paul P.
Boulesteix, Anne-Laure
Saeys, Yvan
Robinson, Mark D.
Essential guidelines for computational method benchmarking
title Essential guidelines for computational method benchmarking
title_full Essential guidelines for computational method benchmarking
title_fullStr Essential guidelines for computational method benchmarking
title_full_unstemmed Essential guidelines for computational method benchmarking
title_short Essential guidelines for computational method benchmarking
title_sort essential guidelines for computational method benchmarking
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6584985/
https://www.ncbi.nlm.nih.gov/pubmed/31221194
http://dx.doi.org/10.1186/s13059-019-1738-8
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