ATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAAGTAC
TGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAACGGTCCTTAAGCTGTATTGCACCATATGACG
GATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTTCGGTCCTTAAGCTGTATTCCTTAACAACGGTCCTTAAGG
ATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAAGTAC
TGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAACGGTCCTTAAGCTGTATTGCACCATATGACG
GATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTTCGGTCCTTAAGCTGTATTCCTTAACAACGGTCCTTAAGG
Snakemake for Scalable and Reproducible Data Analysis
04 January 2021
For-profit: 300 CHF
No future instance of this course is planned yet
Overview
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 text-based workflow specification language and a scalable execution environment, that allows the parallelized execution of workflows on workstations, compute servers and clusters without modification of the workflow definition. Thereby, a scheduling algorithm based on a multidimensional knapsack problem allows Snakemake to maximize workflow execution speed while not exceeding given constraints like the number of available processor cores, cluster nodes or auxilliary hardware like graphics cards.
Since its publication, Snakemake has been widely adopted and was used to build analysis workflows for a variety of high impact publications. With about 5000 homepage visits per month, it has a large and stable user community.
Audience
This course is addressed to bioinformaticians and life scientists interested in learning how to create workflows of data management.
Learning outcomes
This course will introduce the Snakemake workflow definition language. After completing this course, the participants should be able to:
- use the Snakemake execution environment to scale workflows to compute servers and clusters while adapting to hardware specific constraints.
- create reproducible analyses that can be adapted to new data with little effort.
Prerequisites
Knowledge / competencies
Participants should have basic programming skills in Python. You can test your skills in the quiz in this link.
Technical
Participants are required to have a laptop with a command line terminal installed.
Application
The registration fees for academics are 60 CHF and 300 CHF for for-profit companies.
You will be informed by email of your registration confirmation. Upon reception of the confirmation email, participants will be asked to confirm attendance by paying the fees within 5 days.
Applications close as soon as the places will be filled. Deadline for free-of-charge cancellation is set to 04/01/2021. Cancellation after this date will not be reimbursed. Please note that participation in SIB courses is subject to our general conditions.
Venue and Time
This course will be streamed on 18 and 19 January 2021, in the afternoons, start at 13:30 CET and end around 17:00 CET.
Precise information will be provided to the participants in due time.
Additional information
Trainer: Johannes Köster, University of Duisburg-Essen
Coordination: Patricia Palagi
You are welcome to register to the SIB courses mailing list to be informed of all future courses and workshops, as well as all important deadlines using the form here.
Please note that participation in SIB courses is subject to our general conditions.
SIB abides by the ELIXIR Code of Conduct. Participants of SIB courses are also required to abide by the same code.
For more information, please contact training@sib.swiss.