RNA-Seq Data Analysis (Online Hands-on Workshop)

13–16 April 2026 | 6:30 PM IST | Online| Certificate

About the Workshop

This online hands-on workshop introduces participants to RNA-seq data analysis workflows, covering key steps such as data preprocessing, quality control, alignment, and differential gene expression analysis. Through guided sessions and practical exercises, participants will gain experience in analyzing high-throughput sequencing data and interpreting biologically meaningful results.

What You Will Learn

• Fundamentals of RNA-seq and transcriptomics

• Understanding FASTQ data and quality scores

• Quality control using FastQC

• Read trimming and preprocessing using Trimmomatic

• Sequence alignment using HISAT2

• Gene expression quantification using FeatureCounts

• Differential expression analysis using DESeq2

• Data visualization (volcano plots, heatmaps)

• Functional enrichment analysis (GO/KEGG)

Course Features

• Live online hands-on sessions

• e-Certificate upon completion

• Access to session recordings

• Software installation support

• Protocols (PDF) and lecture PPTs provide

  
  

Learning Outcomes

• Perform RNA-seq data preprocessing and quality control

• Conduct alignment and gene expression quantification

• Identify differentially expressed genes (DEGs)

• Visualize and interpret gene expression data

• Apply bioinformatics tools to real-world research problems

  
  

Who Can Join

• Undergraduate and postgraduate students in Life Sciences

• Research scholars and faculty members

• Professionals from Biotechnology, Biochemistry, Microbiology, and related domains

• Medical, Pharmacy, and Chemical Sciences background participants

Course Fee

Indian Participants: ₹1199 INR
International Participants: 75 USD

Workshop Module

Session 1: Introduction to RNA-Seq and Overview of Data

• Overview of RNA-Seq:

• What is RNA-Seq? Applications in differential expression and transcript discovery.

• Overview of the RNA-Seq data analysis workflow.

• Introduction to Raw Data:

• FASTQ format and quality scores.

• Common challenges: low-quality reads, adapter contamination.

Session 2: Preprocessing and Quality Control

• Quality Assessment:

• Quality assessment using FastQC.

• Trimming and Filtering Reads:

• Trimming and filtering reads with Trimmomatic.

• Hands-On:

• Run FastQC on a sample dataset.

• Perform trimming and check results.

Session 3: Alignment and Transcript Quantification

• Read Alignment:

• Reference genome vs. transcriptome alignment.

• Transcript Quantification:

• Gene-level vs. transcript-level quantification.

• Hands-On:

• Align reads to a reference genome using HISAT2.

• Perform transcript quantification with feature Counts.

Session 4 & 5: Differential Expression Analysis and Visualization

• Normalization and Statistical Testing:

• Need for normalization (e.g., TPM, FPKM, counts per million).

• Differential expression analysis using DESeq2.

• Visualization of Results:

• Volcano plots and heatmaps.

• Functional enrichment analysis (e.g., GO/KEGG).

• Hands-On:

• Conduct differential expression analysis with DESeq2.

• Generate a volcano plot and a heatmap.