Pipeliner: A Nextflow-Based Framework for the Definition of Sequencing Data Processing Pipelines.

Nextflow RNA-seq pipeline pipeline development scRNA-seq pipeline sequencing workflows

Journal

Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621

Informations de publication

Date de publication:
2019
Historique:
received: 21 11 2018
accepted: 13 06 2019
entrez: 19 7 2019
pubmed: 19 7 2019
medline: 19 7 2019
Statut: epublish

Résumé

The advent of high-throughput sequencing technologies has led to the need for flexible and user-friendly data preprocessing platforms. The Pipeliner framework provides an out-of-the-box solution for processing various types of sequencing data. It combines the Nextflow scripting language and Anaconda package manager to generate modular computational workflows. We have used Pipeliner to create several pipelines for sequencing data processing including bulk RNA-sequencing (RNA-seq), single-cell RNA-seq, as well as digital gene expression data. This report highlights the design methodology behind Pipeliner that enables the development of highly flexible and reproducible pipelines that are easy to extend and maintain on multiple computing environments. We also provide a quick start user guide demonstrating how to setup and execute available pipelines with toy datasets.

Identifiants

pubmed: 31316552
doi: 10.3389/fgene.2019.00614
pmc: PMC6609566
doi:

Types de publication

Journal Article

Langues

eng

Pagination

614

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Auteurs

Anthony Federico (A)

Bioinformatics Program, Boston University, Boston, MA, United States.
Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, United States.

Tanya Karagiannis (T)

Bioinformatics Program, Boston University, Boston, MA, United States.

Kritika Karri (K)

Bioinformatics Program, Boston University, Boston, MA, United States.

Dileep Kishore (D)

Bioinformatics Program, Boston University, Boston, MA, United States.

Yusuke Koga (Y)

Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, United States.

Joshua D Campbell (JD)

Bioinformatics Program, Boston University, Boston, MA, United States.
Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, United States.

Stefano Monti (S)

Bioinformatics Program, Boston University, Boston, MA, United States.
Division of Computational Biomedicine, Boston University School of Medicine, Boston, MA, United States.

Classifications MeSH