School of Bioinformatics · AI & machine learning
Reproducible Bioinformatics & Pipelines
An analysis that only runs on one laptop is a liability. This course teaches the engineering practices that make bioinformatics reproducible, from version control to workflow managers and containers.
Course overview
Reproducible Bioinformatics & Pipelines covers the engineering practices that let someone else re-run your analysis and get the same result: version control, managed software environments, containers, workflow managers and community pipelines.
You move an analysis from a folder of scripts to a tested, containerised Nextflow pipeline, learn to run and configure nf-core pipelines such as rnaseq and sarek, and finish by releasing code with documentation, a licence and a citable DOI.
Learning outcomes
By the end of the course you will be able to:
- Version-control analyses with Git and GitHub
- Manage software with conda, Docker and Apptainer
- Write workflows in Nextflow
- Run and configure nf-core pipelines
- Test, document and release an analysis with a DOI
Skills you will practise
Eligibility and prerequisites
Who can apply
- Students and graduates of B.Sc., M.Sc., B.Tech., M.Tech., B.Pharm., M.Pharm., MBBS, BDS, B.V.Sc. or a PhD programme in the life sciences, biotechnology, bioinformatics, pharmacy, medicine, agriculture, chemistry, statistics or computer science
- Researchers, faculty and industry professionals moving into data-driven biology
- Final-year students may apply before their results are declared
Prerequisites
- Comfort with the command line
- Python or R scripting
Best suited to
- Bioinformaticians moving from scripts to pipelines
- Students targeting research-software or industry roles
Module-wise syllabus
6 modules. Each pairs instructor-led sessions with a hands-on lab on public data.
Topics
- Git fundamentals
- Branches and pull requests
- Collaborating on GitHub
Topics
- conda and mamba
- Docker and Apptainer
- Pinning versions
Topics
- Why not shell scripts
- Nextflow processes and channels
- Snakemake for comparison
Topics
- Running nf-core/rnaseq and nf-core/sarek
- Configuration and profiles
- Reading MultiQC output
Topics
- Testing scientific code
- Documentation
- Licences, citations and Zenodo DOIs
Topics
- A small Nextflow pipeline
- CI tests
- Release with a DOI
Practical sessions and projects
Capstone project
Ship a reproducible pipeline
Turn an analysis into a tested, containerised Nextflow pipeline that someone else can run with one command, and release it with documentation and a DOI.
Assessed on the correctness of the analysis, the quality of the code and the reasoning in the write-up. A pass is required for the certificate.
- Version control
Put an existing analysis under Git, work on a feature branch and merge it through a reviewed pull request.
- Environments
Pin an analysis environment with conda, build a Docker image for it and run the same image with Apptainer.
- Workflow managers
Rewrite a shell-script analysis as a Nextflow workflow, then compare it with a Snakemake version.
- nf-core
Run nf-core/rnaseq with its test profile, change parameters through a config file and read the MultiQC report.
- Quality and release
Add tests and continuous integration to a pipeline, write its documentation and archive a release on Zenodo.
- Project: a published pipeline
Ship a small, tested Nextflow pipeline that another learner can run with one command.
Software, tools and datasets
Software and tools
All software is free and open source or free for academic use. Recommended computer: 8 GB RAM, 30 GB free disk, Linux, macOS or Windows with WSL2.
Datasets
- nf-core test datasets: Small, realistic inputs for running pipelines quickly.github.com/nf-core/test-datasets
- Your analyses from earlier courses: Material to turn into a reproducible pipeline.Courses on your learning path
Core reading
- Di Tommaso P et al. (2017). Nextflow enables reproducible computational workflows. Nature Biotechnology 35:316–319.
- Ewels PA et al. (2020). The nf-core framework for community-curated bioinformatics pipelines. Nature Biotechnology 38:276–278.
- Wilson G et al. (2017). Good enough practices in scientific computing. PLOS Computational Biology 13:e1005510.
Duration, format and fees
- Next cohort
- Dates are sent with your admission offer
- Timetable
- Three evening or weekend sessions a week (IST), plus a lab clinic; intensive and weekend-only schedules on request
- Payment
- Secure online payment link with your admission offer (UPI, cards, net banking). Instalments on request for fees above ₹15,000.
- Refunds
- See the refund and cancellation policy.
Instructor
The instructor for each cohort is named in your admission offer and on this page when the cohort is announced. Vedicgen instructors are selected for hands-on research or industry experience in the subject they teach, and every course is reviewed by a second subject expert.
Questions about who teaches a cohort? [email protected]
Certificate
Learners who complete the course and pass its capstone receive a Vedicgen certificate of completion for Reproducible Bioinformatics & Pipelines, issued by Vivofold, stating the guided hours and skills assessed. Each certificate has a unique ID and QR code that anyone can check.
Apply for Reproducible Bioinformatics & Pipelines
Apply
Send the form below. It takes about five minutes.
Review
An adviser confirms your fit and format within two working days.
Offer
You receive dates, timetable and a secure payment link.
Onboard
Set-up guide, pre-reading and joining links.
Frequently asked questions
In the live cohort, modules are taught in instructor-led sessions with a weekly lab clinic where you work on real public data with help at hand; every session is recorded. The self-paced format uses the same lessons, labs and datasets with mentor review of your capstone. Both formats end with an assessed project reviewed for the code and the science.
A laptop with at least 8 GB of RAM and about 30 GB of free disk space, running Linux, macOS, or Windows with WSL2. Docker or Apptainer must be installable on the machine. Installation instructions are sent before the first session, and lab clinics help with any set-up problems.
Yes. Learners who complete the course and pass its assessment receive a Vedicgen certificate of completion, issued by Vivofold. Every certificate carries a unique ID and a QR code that anyone, including an employer or admissions office, can check on the certificate verification page.
Apply with the form on this page. Live and in-person cohorts run through the year; the dates, timetable and joining details of the next cohort are sent with your admission offer and listed on this page once announced. Self-paced enrolment opens as soon as your application is accepted.
Yes. No course runs longer than four weeks, and the length is customisable: choose the standard schedule, an intensive one- to two-week schedule, weekends only, or a custom timetable. Pick your preference on the application form; colleges and teams can book their own dates.
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