Reproducibility in Bioinformatics by Sustaining Bioconda Development
Johannes Köster (University of Duisburg-Essen, Bioconda Core Team)
To establish teaching material, improve documentation, and minimize maintenance effort of the Bioconda project by extending automation of code review, testing, and building.
Bioinformatics software comes in a variety of programming languages and requires diverse installation methods. This heterogeneity makes management of a software stack complicated, error-prone, and inordinately time-consuming. Whereas software deployment has traditionally been handled by administrators, ensuring the reproducibility of data analyses requires that the researcher be able to maintain full control of the software environment, rapidly modify it without administrative privileges, and reproduce the same software stack on different machines. The Conda package manager has become an increasingly popular means to overcome these challenges for all major operating systems. Conda allows defining software packages in terms of text-based recipes, which are compiled into relocatable binary packages and can be installed into isolated software environments without the need for administrative privileges. The Bioconda project unlocks Conda’s strengths for bioinformatics by providing thousands of Conda packages, covering almost all relevant bioinformatics tools. It has become a backbone of reproducible data analysis in bioinformatics.