Aim
Next-Generation Sequencing Data Analysis teaches practical NGS analysis from raw reads to results. Learn QC, trimming, alignment, variant calling basics, RNA-seq basics, annotation concepts, and how to report results clearly.
Program Objectives
- NGS Basics: platforms, workflows, and study design concepts.
- Data Formats: FASTQ, BAM/SAM, VCF, GTF/GFF basics.
- QC & Trimming: read quality checks and preprocessing.
- Alignment: mapping reads and evaluating metrics.
- Variant Calling: SNP/indel workflow (intro).
- RNA-seq: counts and differential expression basics (intro).
- Annotation: variant/gene annotation concepts.
- Reporting: plots, tables, and reproducible summaries.
- Capstone: complete a mini NGS analysis project.
Program Structure
Module 1: NGS Workflow and Study Design
- Read types: single-end vs paired-end.
- Coverage, depth, replicates, controls (overview).
- Common applications: WGS/WES, RNA-seq, metagenomics (overview).
- Good data management and metadata basics.
Module 2: Data Formats and Tools Setup
- FASTQ and quality scores.
- SAM/BAM basics and indexing concepts.
- VCF structure basics.
- Toolchain overview: QC, aligners, callers (overview).
Module 3: QC and Read Preprocessing
- QC reports and common read issues.
- Adapter trimming and quality filtering.
- Removing low-quality reads and contamination checks (intro).
- Pre-QC vs post-QC comparisons.
Module 4: Alignment and Post-Processing
- Reference genome choice and indexing (overview).
- Alignment workflow and BAM outputs.
- Sorting, indexing, duplicates (overview).
- Alignment metrics: mapping rate, coverage, depth.
Module 5: Variant Calling and Filtering (Intro)
- Variant calling concepts: SNPs and indels.
- Basic calling workflow (overview).
- Filtering by depth, quality, and allele balance.
- Generating clean variant tables.
Module 6: Variant Annotation and Interpretation (Intro)
- Annotation concepts: gene context and effect (overview).
- Filtering strategies for candidate variants.
- Basic interpretation: quality, impact, and limitations.
- Reporting clinically relevant vs research findings (overview).
Module 7: RNA-seq Analysis (Intro)
- Gene expression workflow overview.
- Counts generation and normalization concepts.
- Differential expression basics and common plots (overview).
- Pathway enrichment concepts (intro).
Module 8: Visualization, Reporting, and Reproducibility
- Key plots: QC summaries, coverage plots, volcano plots (overview).
- Building summary tables and result exports.
- Reproducibility basics: parameters, versions, logs.
- Writing a short methods + results report.
Final Project
- Choose one track: variant calling OR RNA-seq.
- Deliverables: QC + analysis outputs + plots + short report.
- Submit: result folder + report document.
Participant Eligibility
- Students/researchers in Genetics, Biotechnology, Bioinformatics
- Basic molecular biology helpful
- No advanced coding required (workflow-based learning)
Program Outcomes
- Run QC, alignment, and core NGS workflows.
- Generate variant or expression results with basic filtering.
- Create clear plots and summary tables.
- Deliver a reproducible mini NGS project report.
Program Deliverables
- e-LMS Access: lessons, datasets, templates.
- Toolkit: QC checklist, pipeline checklist, report template.
- Assessment: certification after capstone submission.
- e-Certification and e-Marksheet: digital credentials.
Future Career Prospects
- NGS Data Analyst (Trainee)
- Bioinformatics Associate
- Genomics Research Assistant
- Clinical Research Data Associate
Job Opportunities
- Genomics Labs/CROs: NGS analysis and reporting roles.
- Biotech/Pharma: biomarker and sequencing analytics teams.
- Universities: genomics and transcriptomics research groups.
- Hospitals/Research Centers: translational genomics projects.
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