C3780 Bioinformatics Workflow Managers

Faculty of Science
Spring 2026
Extent and Intensity
2/2/0. 5 credit(s). Type of Completion: zk (examination).
In-person direct teaching
Teacher(s)
Nicolas Blavet, Ph. D (lecturer)
Mgr. Vojtěch Bystrý, Ph.D. (lecturer)
doc. RNDr. Radka Svobodová, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Radka Svobodová, Ph.D.
National Centre for Biomolecular Research – Faculty of Science
Contact Person: RNDr. Tomáš Raček, Ph.D.
Supplier department: National Centre for Biomolecular Research – Faculty of Science
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
This course aims to provide students with practical skills in bioinformatics workflow management using management systems such as Galaxy, Nextflow, and Snakemake. The course focuses on: develop skills in workflow writing, automation, and management; enhance workflow design and its implementation using different managers; improve workflow efficiency and reproducibility.
Learning outcomes
Upon completing the course, students will understand the structure and syntax of different workflow managers, including Galaxy, Nextflow, and Snakemake. They will be able to write, design, and implement bioinformatics workflows using these tools, automate and manage bioinformatics pipelines efficiently, and optimize workflows for better performance, scalability, and reproducibility.
Syllabus
Throughout this course, we will provide an overview of different workflow managers, specifically Galaxy, Nextflow, and Snakemake, to examine their advantages, disadvantages, and requirements. The specific features of each workflow manager will be assessed. For Galaxy, we will explore its interface and its use in creating and managing complex bioinformatics pipelines. In the case of the Snakemake workflow management system, we will show the basic syntax for defining rules for the execution of specific processes and its use in developing modular and reproducible workflows. For the Nextflow workflow management system, we will cover its basic syntax and domain-specific language (DSL), with the goal of constructing complex and dynamic workflows. Ultimately, the learning of each selected workflow management system will be coupled with the creation of real complex workflows using real data.
Literature
  • Finotello, F., Calura, E., Risso, D., Hautaniemi, S., & Romualdi, C. (2020). Multi-omic data integration in oncology. Frontiers in oncology, 10.
  • Demirbaga, Ü., Aujla, G. S., Jindal, A., & Kalyon, O. (2024). Big Data Analytics: Theory, Techniques, Platforms, and Applications. Springer Nature
  • Bioinformatics with Python cookbook: use modern Python libraries and applications to solve real-world computational biology problems. Packt Publishing Ltd.
Teaching methods
Student projects, their presentations and discussions.
Assessment methods
The student will be assessed based on a written project proposal (1-2 A4 pages) and a final presentation according to rules that will be specified at the beginning of the semester.
Language of instruction
English
Further Comments
The course is taught annually.
The course is taught every week.
  • Permalink: https://is.muni.cz/course/sci/spring2026/C3780