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Cluster Flow: A user-friendly bioinformatics workflow tool

Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, t...

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Detalles Bibliográficos
Autores principales: Ewels, Philip, Krueger, Felix, Käller, Max, Andrews, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5310375/
https://www.ncbi.nlm.nih.gov/pubmed/28299179
http://dx.doi.org/10.12688/f1000research.10335.2
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author Ewels, Philip
Krueger, Felix
Käller, Max
Andrews, Simon
author_facet Ewels, Philip
Krueger, Felix
Käller, Max
Andrews, Simon
author_sort Ewels, Philip
collection PubMed
description Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.
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spelling pubmed-53103752017-03-14 Cluster Flow: A user-friendly bioinformatics workflow tool Ewels, Philip Krueger, Felix Käller, Max Andrews, Simon F1000Res Software Tool Article Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io. F1000Research 2017-05-02 /pmc/articles/PMC5310375/ /pubmed/28299179 http://dx.doi.org/10.12688/f1000research.10335.2 Text en Copyright: © 2017 Ewels P et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Tool Article
Ewels, Philip
Krueger, Felix
Käller, Max
Andrews, Simon
Cluster Flow: A user-friendly bioinformatics workflow tool
title Cluster Flow: A user-friendly bioinformatics workflow tool
title_full Cluster Flow: A user-friendly bioinformatics workflow tool
title_fullStr Cluster Flow: A user-friendly bioinformatics workflow tool
title_full_unstemmed Cluster Flow: A user-friendly bioinformatics workflow tool
title_short Cluster Flow: A user-friendly bioinformatics workflow tool
title_sort cluster flow: a user-friendly bioinformatics workflow tool
topic Software Tool Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5310375/
https://www.ncbi.nlm.nih.gov/pubmed/28299179
http://dx.doi.org/10.12688/f1000research.10335.2
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