Apply next-generation sequencing analysis across real use cases.
Next-Generation Sequencing (NGS) Data Analysis takes an application-oriented tour of what NGS analysis actually delivers across study types. Building on the core pipeline — QC, alignment and downstream analysis — you see how it adapts to different real applications: variant studies, transcriptomics, microbiome and targeted panels, each with its own considerations. The course emphasises matching analysis to the biological question. You finish able to choose and run the right NGS analysis for a given study type. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
This course covers next-generation sequencing (NGS) data analysis across applications — applying the NGS pipeline to variant, transcriptome, microbiome and other real-world studies.
1. Run the core NGS analysis pipeline.
2. Adapt analysis to variant studies.
3. Apply NGS to transcriptome and microbiome.
4. Handle targeted and panel sequencing.
5. Match analysis to the biological question.
• Genomics and molecular-biology researchers
• Bioinformatics students and staff
• Lab and core-facility analysts
• Anyone applying NGS to research
• The ability to run application-specific NGS analysis.
• A study-type-aware perspective.
• A practical genomics skill set.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
Analyze the molecular mechanisms of DNA replication, transcription, and mutation to interpret how sequencing errors propagate in NGS platforms • Evaluate the architectural differences between Illumina short-read, PacBio long-read, and Oxford Nanopore sequencing technologies for experimental selection • Calculate coverage depth, read length distributions, and error profiles using FASTQC and MultiQC to assess raw sequencing data quality
Design end-to-end wet-lab workflows including DNA/RNA extraction, library preparation, and quality control for whole-genome and targeted sequencing • Troubleshoot common protocol failures such as adapter dimer formation, PCR amplification bias, and sample cross-contamination using gel electrophoresis and qPCR validation • Execute standardized sample tracking, batch recording, and chain-of-custody documentation to ensure reproducible multi-center sequencing studies
Construct automated variant calling pipelines using BWA-MEM for alignment, GATK HaplotypeCaller for SNP/indel detection, and ANNOVAR for functional annotation • Develop reproducible analysis environments by containerizing workflows with Docker/Singularity and orchestrating pipelines with Snakemake or Nextflow • Visualize genomic data tracks, coverage profiles, and structural variants using Integrative Genomics Viewer (IGV) and UCSC Genome Browser for manual curation
Calculate statistical power and sample sizes for case-control, cohort, and family-based sequencing studies using tools like GATK-SV or power calculators • Design balanced experimental layouts with proper randomization, blocking, and batch effect controls to minimize confounding in multi-lane sequencing runs • Formulate falsifiable hypotheses and define primary/secondary endpoints aligned with FAIR data principles for publishable NGS research
Integrate multi-omics datasets by combining RNA-seq expression quantification with ChIP-seq peak calling and ATAC-seq chromatin accessibility analysis • Apply machine learning classifiers such as random forests and deep neural networks to predict disease phenotypes from variant burden scores and pathway enrichment data • Interpret clonal evolution trajectories and tumor mutational burden from single-cell and bulk whole-exome sequencing in precision oncology contexts
Navigate CLIA/CAP accreditation requirements, FDA guidance on NGS-based diagnostics, and GDPR/HIPAA frameworks for genomic data privacy • Evaluate informed consent protocols for secondary use of genomic data, return of incidental findings, and data sharing through controlled-access repositories like dbGaP • Implement cybersecurity measures including encryption, access logging, and de-identification pipelines to protect sensitive human genomic datasets
Assess commercial NGS service models, diagnostic assay development timelines, and regulatory submission strategies from Illumina, Thermo Fisher, and emerging biotech case studies • Analyze cost-per-sample economics, turnaround time optimization, and CLIA-lab operational workflows for clinical and pharmaceutical NGS deployment • Construct professional portfolios demonstrating end-to-end project ownership, cross-functional collaboration, and stakeholder communication for biotech hiring managers
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | GATK |
| Covered Tool / Platform | BWA |
| Covered Tool / Platform | SAMtools |
| Covered Tool / Platform | bcftools |
| Covered Tool / Platform | ANNOVAR |
| Covered Tool / Platform | Snakemake |
| Covered Tool / Platform | Nextflow |
| Covered Tool / Platform | Docker |
Based on 0 scholar submissions
No verified reviews published yet. Be the first to share your academic experience.
Your rating will help prospective scholars. Ratings below 3 stars are routed privately to the faculty mentor for immediate response.