School of Bioinformatics · Genomics & transcriptomics
NGS Data Analysis with Galaxy (No Coding)
Galaxy is a free, web-based platform used by thousands of laboratories to run standard bioinformatics tools through a browser. This course teaches the same analyses that command-line courses cover, in a point-and-click environment that records every step.
Course overview
NGS Data Analysis with Galaxy is designed for wet-lab biologists, clinicians and students who need to analyse their own sequencing data now, before (or instead of) learning to program. You work on the public Galaxy servers, so nothing needs to be installed.
The emphasis is on understanding what each tool does and how to judge its output, so the skills carry over if you later move to the command line. You finish by turning your analysis into a Galaxy workflow that can be shared, published and re-run on new samples.
Learning outcomes
By the end of the course you will be able to:
- Upload, organise and quality-check sequencing data in Galaxy
- Trim, align and inspect reads against a reference genome
- Call and filter variants and visualise them in a genome browser
- Run an RNA-seq differential-expression analysis end to end
- Build, share and re-run Galaxy workflows
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
- Basic molecular biology
- No programming
Best suited to
- Wet-lab researchers with sequencing data to analyse
- Students who want to understand NGS analysis before learning to code
- Clinicians and faculty who supervise sequencing projects
Module-wise syllabus
6 modules. Each pairs instructor-led sessions with a hands-on lab on public data.
Topics
- Histories, datasets and tools
- FASTQ and quality scores
- Importing data from SRA
Topics
- Adapter and quality trimming
- Mapping with BWA-MEM and Bowtie2
- Reading alignment statistics
Topics
- Calling with FreeBayes
- Filtering by depth and quality
- Viewing variants in IGV and JBrowse
Topics
- Alignment with HISAT2 and counting with featureCounts
- Differential expression with DESeq2
- Volcano plots and enrichment
Topics
- Extracting workflows from histories
- Parameters and annotations
- Sharing and publishing
Topics
- Choosing a public dataset
- Documenting decisions
- Reporting results
Practical sessions and projects
Capstone project
A shareable Galaxy analysis
Choose a public dataset, analyse it as a documented Galaxy workflow, and present the results with a clear statement of what the analysis can and cannot show.
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.
- Galaxy and sequencing data
Import a public bacterial sequencing run into a Galaxy history and run FastQC and MultiQC on it.
- Cleaning and mapping reads
Trim the reads, map them to the reference and judge the mapping from samtools statistics and coverage plots.
- Variant calling
Call variants in a resistant bacterial isolate and confirm the key mutations visually.
- RNA-seq in Galaxy
Run a complete differential-expression analysis on a public RNA-seq experiment and interpret the top genes.
- Workflows and reproducibility
Turn the RNA-seq analysis into a workflow and re-run it on a second dataset with one click.
- Project: analyse your own question
Analyse a public NGS dataset of your choice in Galaxy and present the workflow, results and limitations.
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
- Mycobacterium tuberculosis resistant isolate reads: Variant-calling practical.NCBI SRA (public)
- Galaxy Training Network RNA-seq data: Differential-expression practical.training.galaxyproject.org (CC-BY)
Core reading
- The Galaxy Community (2024). The Galaxy platform for accessible, reproducible, collaborative data analyses: 2024 update. Nucleic Acids Research 52:W83–W94.
- Galaxy Training Network materials (training.galaxyproject.org).
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 NGS Data Analysis with Galaxy (No Coding), 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 NGS Data Analysis with Galaxy (No Coding)
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
No. You work on the free public Galaxy servers in a web browser. A stable internet connection is enough.
Yes. The tools and parameters are the same ones used on the command line, so the NGS Data Analysis and RNA-seq courses build directly on this one.
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.
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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