Dresden 2020 – scientific programme

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CPP: Fachverband Chemische Physik und Polymerphysik

CPP 66: Focus Session: Big Data in Aquisition in ARPES (joint session O/CPP)

CPP 66.7: Invited Talk

Wednesday, March 18, 2020, 12:15–12:45, REC C 213

Reproducible data analysis with Snakemake — •Johannes Köster — Algorithms for reproducible bioinformatics, Genome Informatics, Institute of Human Genetics, University of Duisburg-Essen, Hufelandstr. 55, 45147 Essen Germany

Data analyses usually entail the application of many command line tools or scripts to transform, filter, aggregate or plot data and results. With ever increasing amounts of data being collected in science, reproducible and scalable automatic workflow management becomes increasingly important. Snakemake is a workflow management system, consisting of a clean, human-readable, text-based workflow specification language and a scalable execution environment, that allows the parallelized execution of workflows on workstations, compute servers, clusters and the cloud without modification of the workflow definition. Snakemake is hugely popular and was used to build analysis workflows for numerous high impact publications. With about 350 citations in the last two years, it is one of the leading frameworks for reproducible data science. This talk will show how Snakemake can be used to easily document, execute, and reproduce data analyses.