School of Bioinformatics · Genomics & transcriptomics
NGS Data Analysis: WGS & WES
Next-generation sequencing produces the data behind most modern genetics. This course takes you through a complete germline variant-calling workflow on whole-genome and whole-exome data, and shows how to check that every step worked.
Course overview
NGS Data Analysis covers germline variant discovery from whole-genome and whole-exome sequencing, following the workflow used in research groups and core facilities: quality control, alignment, duplicate marking, variant calling, filtering and annotation.
Each step is taught with the quality metric that shows whether it worked, so you can recognise a contaminated library, a failed capture or a batch of false-positive calls before they reach a results table. The labs use Genome in a Bottle reference samples, for which the true variants are known, so your call sets are measured against a truth set rather than judged by eye.
Learning outcomes
By the end of the course you will be able to:
- Assess and clean raw reads with FastQC, MultiQC and fastp
- Align reads with BWA-MEM and process BAM files with SAMtools
- Call variants following GATK best practices, and with bcftools
- Filter and annotate variants with VEP and population databases
- Measure precision and recall against a truth set and explain coverage metrics to a reviewer
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
- Bioinformatics Foundations or equivalent
- Comfort with the Linux command line
Best suited to
- Students who know the basics of bioinformatics and the command line
- Researchers with sequencing data from a core facility or provider
- Anyone aiming for a genomics role in research or industry
Module-wise syllabus
6 modules. Each pairs instructor-led sessions with a hands-on lab on public data.
Topics
- Illumina, Oxford Nanopore and PacBio
- Library preparation and its biases
- Study design: depth, coverage and replicates
Topics
- FastQC and MultiQC reports
- Adapter and quality trimming
- Contamination checks
Topics
- Reference genomes and indexing
- BWA-MEM and minimap2
- Duplicates, sorting and BAM statistics
Topics
- GATK HaplotypeCaller and joint genotyping
- bcftools as an alternative caller
- Base-quality recalibration
Topics
- Hard filters and VQSR
- VEP and SnpEff
- ClinVar, gnomAD and population frequency
Topics
- End-to-end workflow
- IGV review of candidate variants
- Writing the methods section
Practical sessions and projects
Capstone project
Find and defend a candidate variant
Run a full workflow on a public exome dataset, prioritise variants, and defend the final candidate with evidence from read-level review and population and clinical databases.
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.
- Sequencing technologies
Compare the read-length and error profiles of short- and long-read data, and estimate the depth a given study design needs.
- Quality control
Run FastQC and fastp on raw reads, interpret every MultiQC panel and decide which samples to trim or exclude.
- Read alignment
Index a reference, align reads with BWA-MEM, mark duplicates and report mapping and coverage statistics.
- Variant calling
Call variants on a Genome in a Bottle exome subset with GATK and with bcftools, and compare the two call sets.
- Filtering and annotation
Filter calls, annotate them with VEP and measure precision and recall against the GIAB truth set.
- Project: an exome case study
Run the full workflow on a public exome, prioritise candidate variants and review each one in IGV before reporting it.
Software, tools and datasets
Software and tools
All software is free and open source or free for academic use. 16 GB of RAM is recommended; full-genome steps are run on subsets sized for a laptop.
Datasets
- Genome in a Bottle HG001 (NA12878): Variant calling against a known truth set.NIST Genome in a Bottle, exome and chromosome subsets
- GRCh38 reference genome: Alignment and annotation.Genome Reference Consortium, via Ensembl or NCBI
- ClinVar and gnomAD: Clinical significance and population frequency of candidates.NCBI ClinVar; gnomAD
Core reading
- Li H (2013). Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv:1303.3997.
- Van der Auwera GA, O’Connor BD. Genomics in the Cloud: Using Docker, GATK, and WDL in Terra. O’Reilly, 2020.
- Danecek P et al. (2021). Twelve years of SAMtools and BCFtools. GigaScience 10:giab008.
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: WGS & WES, 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: WGS & WES
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
Exercises are sized to run on a laptop: whole-genome steps are run on chromosome subsets, and the course explains how the same commands scale on a server or in the cloud.
No. The course teaches research-grade germline analysis. Clinical reporting requires accredited laboratories and additional standards that are outside its scope.
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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