NGS and Transcriptomic Data Analysis: From Raw Reads to Biological Insights

Introduction to the Course

Course Objectives

• Understand the basics of next-generation sequencing (NGS) and RNA-Seq and their applications in transcriptomics.
• Learn how to preprocess and clean raw RNA-Seq data for quality control and alignment.
• Gain hands-on skills in transcript assembly, gene expression analysis, and differential expression using popular tools.
• Master methods for data normalization, filtering, and statistical analysis in RNA-Seq studies.
• Explore how to interpret biological results such as gene ontology enrichment, pathway analysis, and gene regulatory networks.
• Develop the ability to conduct RNA-Seq analyses independently, from raw data to biological interpretation.

What Will You Learn (Modules)

Module 1 — NGS & RNA‑Seq Fundamentals

• Understand sequencing data formats, experimental design fundamentals, and initial quality assessment of raw reads.

Module 2 — QC, Trimming, Alignment & Quantification

• Learn how to control data quality, trim reads, and generate gene/transcript expression counts using trusted bioinformatics tools.

Module 3 — Differential Expression & Insights

• Master differential expression workflows, interpret statistical results, and connect gene-level changes to biological pathways and functional mechanisms.

Who Should Take This Course?

This course is ideal for:

• Bioinformaticians and computational biologists working with genomic or transcriptomic data
• Genomics researchers focusing on RNA-Seq or gene expression analysis
• Biologists, biochemists, and geneticists who wish to gain computational tools for RNA-Seq data analysis
• Students in bioinformatics, genomics, or systems biology programs

Job Opportunities

After completing this course, learners can pursue roles such as:

• Bioinformatics Analyst (RNA-Seq)
• Computational Biologist
• Genomics Researcher
• Transcriptomics Specialist

Why Learn With Nanoschool?

At NanoSchool, we focus on career-relevant learning that builds real capability—not just theory.

• Expert-led training: Learn from instructors with real-world experience in applying skills to industry and research problems.
• Practical & hands-on approach: Build skills through guided activities, templates, and task-based learning you can apply immediately.
• Industry-aligned curriculum: Course content is designed around current tools, workflows, and expectations from employers.
• Portfolio-ready outcomes: Create outputs you can showcase in interviews, academic profiles, proposals, or real work.
• Learner support: Get structured guidance, clear learning paths, and support to stay consistent and finish strong.

Key outcomes of the course

Upon completion, learners will be able to:

• Practical experience in gene expression analysis, transcript assembly, and alternative splicing detection
• Comfort level with the application of DESeq2, EdgeR, and StringTie software packages for RNA-Seq analysis
• In-depth knowledge of biological interpretation of RNA-Seq data for gene discovery, pathway analysis, and biomarker identification
• Portfolio-ready project to showcase your skills in transcriptomic data analysis