Reproducible, scalable, and shareable analysis pipelines with bioinformatics workflow managers

The rapid growth of high-throughput technologies has transformed biomedical research. With the increasing amount and complexity of data, scalability and reproducibility have become essential not just for experiments, but also for computational analysis. However, transforming data into information in...

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Vydáno v:Nature methods Ročník 18; číslo 10; s. 1161 - 1168
Hlavní autoři: Wratten, Laura, Wilm, Andreas, Göke, Jonathan
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Nature Publishing Group 01.10.2021
Témata:
Bioinformatics
Biomedical research
Biomedical Research - methods
Biomedical Research - standards
Complexity
Computational Biology - methods
Computer applications
Medical research
Optimization
Pipelines
Reproducibility
Reproducibility of Results
Workflow
ISSN:1548-7091, 1548-7105, 1548-7105
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Shrnutí:The rapid growth of high-throughput technologies has transformed biomedical research. With the increasing amount and complexity of data, scalability and reproducibility have become essential not just for experiments, but also for computational analysis. However, transforming data into information involves running a large number of tools, optimizing parameters, and integrating dynamically changing reference data. Workflow managers were developed in response to such challenges. They simplify pipeline development, optimize resource usage, handle software installation and versions, and run on different compute platforms, enabling workflow portability and sharing. In this Perspective, we highlight key features of workflow managers, compare commonly used approaches for bioinformatics workflows, and provide a guide for computational and noncomputational users. We outline community-curated pipeline initiatives that enable novice and experienced users to perform complex, best-practice analyses without having to manually assemble workflows. In sum, we illustrate how workflow managers contribute to making computational analysis in biomedical research shareable, scalable, and reproducible.
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ISSN:1548-7091
1548-7105
1548-7105
DOI:10.1038/s41592-021-01254-9