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Next-Generation Sequencing Data Analysis using Galaxy Platform Course

INR ₹2,499.00 INR ₹24,999.00Price range: INR ₹2,499.00 through INR ₹24,999.00

This program comprehensively introduces Next-Generation Sequencing (NGS) data analysis using the Galaxy platform. Participants will gain hands-on experience in quality control, sequence alignment, variant calling, and bioinformatics workflows, equipping them for real-world genomics research.

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Aim

Next-Generation Sequencing Data Analysis using Galaxy Platform teaches practical NGS analysis using Galaxy’s web-based workflows. Learn QC, trimming, alignment, variant calling basics, RNA-seq basics, workflow building, and reproducible reporting without heavy coding.

Program Objectives

  • Galaxy Basics: histories, datasets, tools, workflows, sharing.
  • NGS Formats: FASTQ, BAM, VCF, GTF/GFF basics.
  • QC & Trimming: quality reports and cleanup.
  • Alignment: mapping reads and checking metrics.
  • Variant Calling: SNP/indel workflow concepts (intro).
  • RNA-seq: counts, differential expression basics (intro).
  • Visualization: plots, genome browser tracks, reports.
  • Reproducibility: workflow export, parameters, provenance.
  • Capstone: build and share a complete Galaxy workflow.

Program Structure

Module 1: Galaxy and NGS Foundations

  • Galaxy interface: histories, datasets, tool panel.
  • Uploading data and managing libraries (overview).
  • NGS study design: samples, replicates, metadata.
  • File formats and basic validation.

Module 2: Read QC and Preprocessing

  • FASTQ QC and summary reports.
  • Adapter trimming and quality filtering.
  • Read collapsing, contamination checks (intro).
  • QC checklist for clean input reads.

Module 3: Alignment and Post-Processing

  • Choosing reference genomes and indexes (overview).
  • Alignment workflows and outputs (BAM).
  • Sorting, indexing, duplicates (overview).
  • Alignment QC: coverage, mapping rate, flags.

Module 4: Variant Calling Workflow (Intro)

  • Variant calling concepts and VCF fields.
  • SNP/indel calling steps (overview).
  • Filtering by depth, quality, and allele balance.
  • Simple annotation and variant tables (intro).

Module 5: RNA-seq Analysis Workflow (Intro)

  • Read mapping for RNA-seq and gene models.
  • Counting reads and normalization concepts.
  • Differential expression basics (overview).
  • Heatmaps, PCA, volcano plots (overview).

Module 6: Metagenomics Basics (Optional Intro)

  • 16S/shotgun overview and common outputs.
  • Quality filtering and taxonomic profiling (overview).
  • Basic diversity concepts (intro).
  • Reporting and interpretation limits.

Module 7: Workflow Building and Reproducibility

  • Creating workflows from histories.
  • Setting parameters and tool versions.
  • Batch analysis with collections (overview).
  • Sharing workflows and generating reusable templates.

Module 8: Visualization and Reporting

  • Genome browser tracks and inspection (overview).
  • Creating summary tables and plots.
  • Exporting results and building a short analysis report.
  • Good reporting: methods, parameters, QC, limitations.

Final Project

  • Choose one dataset: variant calling OR RNA-seq.
  • Build a complete Galaxy workflow with QC + analysis + outputs.
  • Deliverables: workflow file + key plots/tables + short report.
  • Submit: shared history/workflow link (or exported files) + report.

Participant Eligibility

  • Students/researchers in Bioinformatics, Genetics, Biotechnology
  • Beginners who want NGS analysis without heavy coding
  • Basic genomics concepts helpful

Program Outcomes

  • Navigate Galaxy and manage NGS datasets.
  • Run QC, alignment, and core NGS workflows.
  • Build reproducible Galaxy workflows and reports.
  • Create a portfolio-ready Galaxy project.

Program Deliverables

  • e-LMS Access: lessons, datasets, workflow templates.
  • Toolkit: Galaxy workflow checklist, QC guide, report template.
  • Assessment: certification after project submission.
  • e-Certification and e-Marksheet: digital credentials.

Future Career Prospects

  • NGS Data Analyst (Trainee)
  • Bioinformatics Associate
  • Genomics Research Assistant
  • Clinical Research Data Assistant

Job Opportunities

  • Genomics Labs/CROs: routine NGS analysis and reporting.
  • Universities: genomics and transcriptomics projects.
  • Biotech/Pharma: biomarker and sequencing analytics teams.
  • Hospitals/Research Centers: translational genomics research groups.
Category

E-LMS, E-LMS+Videos, E-LMS+Videos+Live Lectures

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