Jupyter and Galaxy: Easing entry barriers into complex data analyses for biomedical researchers

Björn A. Grüning, Eric Rasche, Boris Rebolledo-Jaramillo, Carl Eberhard, Torsten Houwaart, John Chilton, Nate Coraor, Rolf Backofen, James Taylor, Anton Nekrutenko

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

What does it take to convert a heap of sequencing data into a publishable result? First, common tools are employed to reduce primary data (sequencing reads) to a form suitable for further analyses (i.e., the list of variable sites). The subsequent exploratory stage is much more ad hoc and requires the development of custom scripts and pipelines, making it problematic for biomedical researchers. Here, we describe a hybrid platform combining common analysis pathways with the ability to explore data interactively. It aims to fully encompass and simplify the "raw data-to-publication" pathway and make it reproducible.

Original languageEnglish (US)
Article numbere1005425
JournalPLoS computational biology
Volume13
Issue number5
DOIs
StatePublished - May 2017

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Galaxies
Publications
Pipelines
researchers
Research Personnel
Sequencing
Pathway
Heap
Convert
Simplify

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

Cite this

Grüning, Björn A. ; Rasche, Eric ; Rebolledo-Jaramillo, Boris ; Eberhard, Carl ; Houwaart, Torsten ; Chilton, John ; Coraor, Nate ; Backofen, Rolf ; Taylor, James ; Nekrutenko, Anton. / Jupyter and Galaxy : Easing entry barriers into complex data analyses for biomedical researchers. In: PLoS computational biology. 2017 ; Vol. 13, No. 5.
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Grüning, BA, Rasche, E, Rebolledo-Jaramillo, B, Eberhard, C, Houwaart, T, Chilton, J, Coraor, N, Backofen, R, Taylor, J & Nekrutenko, A 2017, 'Jupyter and Galaxy: Easing entry barriers into complex data analyses for biomedical researchers', PLoS computational biology, vol. 13, no. 5, e1005425. https://doi.org/10.1371/journal.pcbi.1005425

Jupyter and Galaxy : Easing entry barriers into complex data analyses for biomedical researchers. / Grüning, Björn A.; Rasche, Eric; Rebolledo-Jaramillo, Boris; Eberhard, Carl; Houwaart, Torsten; Chilton, John; Coraor, Nate; Backofen, Rolf; Taylor, James; Nekrutenko, Anton.

In: PLoS computational biology, Vol. 13, No. 5, e1005425, 05.2017.

Research output: Contribution to journalArticle

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AU - Houwaart, Torsten

AU - Chilton, John

AU - Coraor, Nate

AU - Backofen, Rolf

AU - Taylor, James

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