Title
Jupyter and Galaxy: Easing entry barriers into complex data analyses for biomedical researchers.
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.
Year
DOI
Venue
2017
10.1371/journal.pcbi.1005425
PLOS COMPUTATIONAL BIOLOGY
Field
DocType
Volume
Data processing,Biology,Complex data type,Heap (data structure),Barriers to entry,Bioinformatics,Genetics,Scripting language
Journal
13
Issue
ISSN
Citations 
5
1553-734X
1
PageRank 
References 
Authors
0.38
5
10
Name
Order
Citations
PageRank
Björn A. Grüning1288.46
Eric Rasche2392.43
Boris Rebolledo-Jaramillo310.38
Carl Eberhard4392.10
Torsten Houwaart571.55
John Chilton6533.27
Nate Coraor7392.10
Rolf Backofen81213104.30
James Taylor931926.37
Anton Nekrutenko1021.49