RT Journal Article SR Electronic T1 Enhancing pre-defined workflows with ad hoc analytics using Galaxy, Docker and Jupyter JF bioRxiv FD Cold Spring Harbor Laboratory SP 075457 DO 10.1101/075457 A1 Björn A. Grüning A1 Eric Rasche A1 Boris Rebolledo-Jaramillo A1 Carl Eberhard A1 Torsten Houwaart A1 John Chilton A1 Nate Coraor A1 Rolf Backofen A1 James Taylor A1 Anton Nekrutenko YR 2016 UL http://biorxiv.org/content/early/2016/09/16/075457.abstract AB 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., list of variable sites). The subsequent exploratory stage is much more ad hoc and requires development of custom scripts making it problematic for biomedical researchers. Here we describe a hybrid platform combining common analysis pathways with exploratory environments. It aims at fully encompassing and simplifying the “raw data-to-publication” pathway and making it reproducible.