Programme Parameters
Graduate / Intermediate
3 Days (4.5 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
RNA sequencing (RNA-Seq) has revolutionized transcriptomics by enabling researchers to study gene expression comprehensively and quantitatively. This course offers an in‑depth introduction to RNA-Seq data analysis, focusing on Differential Gene Expression (DGE) workflows using real‑life datasets and open‑source bioinformatics tools. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
RNA sequencing (RNA-Seq) has revolutionized transcriptomics by enabling researchers to study gene expression comprehensively and quantitatively. This course offers an in‑depth introduction to RNA-Seq data analysis, focusing on Differential Gene Expression (DGE) workflows using real‑life datasets and open‑source bioinformatics tools.
📋 Course Objectives
1. Apply biotechnology methods to authentic research and industry problems.
2. Assemble a documented case study that evidences your applied capability.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in biotechnology
• R&D engineers and working professionals applying biotechnology in industry
• Academics and educators building research or teaching capacity in biotechnology
🚀 Key Learning Outcomes
• A demonstrable biotechnology project for your research or industry portfolio.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Day 1 – Foundations of RNA‑Seq
Understand the RNA‑Seq workflow and DGE concepts • Acquire raw data and explore common file formats • Perform sequence quality checks using FastQC
Day 2 – Mapping & Normalisation
Map reads to a reference genome with HISAT2 • Quantify gene‑level counts using featureCounts • Apply count‑normalisation techniques (e.g., size‑factor)
Day 3 – Differential Expression & Interpretation
Conduct differential expression analysis with DESeq2 • Visualise results using heat maps and volcano plots in R/ggplot2 • Perform functional enrichment and pathway analysis
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | FastQC |
| Covered Tool / Platform | HISAT2 |
| Covered Tool / Platform | featureCounts |
| Covered Tool / Platform | DESeq2 |
| Covered Tool / Platform | ggplot2 |
| Covered Tool / Platform | pheatmap |
| Covered Tool / Platform | clusterProfiler |
Frequently Asked Questions
Scholar Feedback & Reviews
Based on 0 scholar submissions
Rating Breakdown
No verified reviews published yet. Be the first to share your academic experience.
Leave Scholar Feedback
Your rating will help prospective scholars. Ratings below 3 stars are routed privately to the faculty mentor for immediate response.
