Advanced Certificate Programme in NGS Data Analysis | Bioinformatics, Variant Calling & Multi-Omics
About the
Programme
The Advanced Certificate Programme in NGS Data Analysis is a comprehensive 100 Hrs(3 Months) online programme designed to train learners in Next-Generation Sequencing (NGS), Variant analysis, Transcriptomics, Proteomics, and Epigenomics. The programme blends biological principles with computational data science, offering hands-on experience using R, Bash, and other leading bioinformatics tools.
Learners will perform real omics data analysis—from raw FASTQ files to biological interpretation—using tools such as FastQC, BWA, samtools, GATK, bcftools, ANNOVAR, VEP, SnpEff, DESeq2, and more.
The programme concludes with integrative multi-omics, reporting, and employability training for industry-ready bioinformaticians and genomics professionals
This Programme is offered by the School of Biotechnology & Bioinformatics, D. Y. Patil Deemed to be University, Navi Mumbai in Academic Collaboration with BRAASK Education Pvt. Ltd. (TechMedBuddy) – A Skill India Certified Company.
Programme
Highlights
Hands-on NGS certification: learn alignment, variant calling, RNA-Seq, exome analysis, multi-omics integration, reporting, and ethics for genomic data science.
The following employable Skills will be acquired after successful completion of the programme:
| Skill Category | Description | Key Skills |
| NGS Data Processing & QC | Core skills for handling raw sequencing data, ensuring read quality, and preparing datasets for downstream analysis. | FastQC, MultiQC, Trimmomatic, FASTQ/BAM/VCF Handling, Read Quality Metrics, Adapter Trimming |
| Alignment & Variant Calling Pipelines | Building complete NGS workflows for short- and long-read sequencing, mutation detection, and structural variant discovery. | BWA, samtools, GATK, bcftools, FreeBayes, Mutect2, Minimap2, Longshot, Medaka |
| Variant Annotation & Interpretation | Annotating mutations for biological and clinical relevance, integrating public genomic databases, and generating reports. | ANNOVAR, VEP, SnpEff, gnomAD, ClinVar, COSMIC, IGV Visualization, Functional Annotation |
| Transcriptomics& Gene Expression Analysis | Skills to process RNA-Seq or microarray data, detect differentially expressed genes, and perform pathway enrichment. | DESeq2, edgeR, limma, GO/KEGG/Reactome, Count Matrices, Normalization, Pathway Analysis |
| Exome & CNV Analysis | Clinical-grade variant identification and copy-number detection for rare disease and cancer applications. | WES Workflows, HaplotypeCaller, ExomeDepth, XHMM, Clinical Databases, Reporting |
| Multi-Omics & Machine Learning | Integration of genomic, transcriptomic, and image-based data for biomarker discovery and predictive modeling. | DIABLO, MOFA, PCA, Clustering, Classification, Feature Selection, scikit-learn (intro) |
| Workflow Automation & Reproducibility | Writing scripts, version-controlling analyses, and creating portable pipelines suitable for research and diagnostics. | R/Bash Scripting, Git/GitHub, RMarkdown Reporting, Reproducible Pipelines, Workflow Documentation |
| Ethics & Regulatory Compliance | Responsible handling of human genomic data in clinical and research environments. | HIPAA, GDPR, ELSI, Data Privacy, Consent, Secure Data Sharing |
Industry Tools & Technologies
| Tool/Technology | Tool/Technology | Tool/Technology |
| FastQC / MultiQC | BWA • samtools • GATK | bcftools • FreeBayes • HaplotypeCaller
|
| VEP • ANNOVAR • SnpEff | IGV (Visualization) | Minimap2 • Longshot • Medaka (Long-Read Pipelines)
|
| DESeq2 • edgeR • limma | GO / KEGG / Reactome | ExomeDepth • XHMM (CNV Detection)
|
| R • RStudio • Bash • Linux | RMarkdown • ggplot2 | Git • GitHub • Reproducibility Tools
|
| scikit-learn (Intro) | Bioinformatics File Formats (FASTQ, BAM, VCF, GTF) | Public Genomic Databases (gnomAD, ClinVar, COSMIC)
|
Programme
Duration
3 Months (100 Hours- Online). The First batch of the programme will commence from 28 November 2025.
Programme
Eligibility
The Advanced Certificate Programme in NGS Data Analysis welcomes students and professionals who want to build expertise in sequencing data processing, genomics, and bioinformatics workflows for research, diagnostics, and precision medicine.
| Criteria | Detail |
| Educational Background | Ongoing or Completed Undergraduate or postgraduate students (B.Sc./M.Sc. / B.Tech./M.Tech.) in Life Sciences, Biotechnology, Bioinformatics, Genetics, Microbiology, Biochemistry, Molecular Biology, or related biological disciplines. |
| Professional Experience | Working professionals in healthcare, molecular diagnostics, pharma/biotech, computational biology, or research labs looking to transition into NGS and bioinformatics roles. |
| Domain Flexibility | Medical, pharmaceutical, computational, or data science professionals seeking to apply NGS, variant calling, or RNA-Seq in their domain. |
| Advanced Academics | Ph.D. scholars and research scientists conducting genomics or omics-driven studies, aiming to learn standardized sequencing pipelines and clinical interpretation. |
No prior programming required — R and Bash will be introduced from basics.
Ideal for students, researchers, and industry professionals aiming for genomics careers.
Programme
Fees
Programme Fee:INR 25,000 Fee includes access to all learning materials, practical labs, datasets, hands-on R/Bash sessions, assessments, and certificate upon successful completion.
| Timeline | Detail |
| Program Start Date | 28 November 2025 |
| Application Deadline | Applications are accepted on a rolling basis until seats are filled. |
Scholarships
Up to 50% Scholarship in Programme feeis available for Students and Alumni of D Y Patil Deemed to be University, Navi Mumbai
Programme
Objectives
Upon successful completion, learners will be able to:
- Explain NGS platforms, sequencing technologies, and omics data formats (FASTQ, BAM, VCF, GTF)
- Manage and preprocess raw sequencing data using FastQC, MultiQC, BWA, STAR, HISAT2, samtools, and GATK, HTSeq
- Perform variant calling, filtration, and annotation using bcftools, FreeBayes, ANNOVAR, VEP, and SnpEff
- Conduct gene expression and enrichment analysis using DESeq2, edgeR, limma, KEGG, GO, and Reactome, Network Analysis
- Execute exome sequencing workflows, detect CNVs, and interpret clinical variants
- Apply multi-omics integration and basic machine learning for biomarker discovery
- Communicate findings through professional visualizations and reproducible reports
- Follow ethical and regulatory standards for genomic data (HIPAA, GDPR, ELSI)
Syllabus
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