Transcriptome Library Preparation and Data Analysis: From RNA Extraction to Bioinformatics Interpretation

Introduction to the Course

Course Objectives

• Learn how to extract RNA, evaluate RNA quality, and prepare high-quality RNA libraries for sequencing.
• Gain practical experience in RNA-Seq library preparation procedures and various approaches of sequencing technologies.
• Master the application of bioinformatics tools to analyze transcriptomic data, including quality assessment, differential expression analysis, and functional annotation.
• Delve into the concept of combining transcriptomic data with other omics disciplines (such as genomics and proteomics) for a holistic view of gene expression regulation.
• Develop the skill to interpret RNA-Seq analysis output and create graphical representations such as heatmaps, volcano plots, and gene expression profiles.

What Will You Learn (Modules)

Module 1 — RNA Extraction & Quality Control

• Learn the foundational lab techniques for extracting high‑quality RNA and assessing its integrity—critical for successful RNA‑Seq.

 Module 2: Advanced AI Techniques for Hazard Detection

• Explore library construction workflows, adapter ligation, amplification, and sequencing readiness practices for transcriptome projects.

Module 3 — RNA‑Seq Bioinformatics & Interpretation

• Process raw reads, align or quantify expression, perform differential expression analysis, create visualizations (heatmaps/volcano plots), and obtain functional insights.

Who Should Take This Course?

This course is ideal for:

• Researchers in genomics, transcriptomics, or molecular biology who need to understand RNA-Seq data and bioinformatics analysis.
• Bioinformaticians looking to expand their expertise in transcriptomic data analysis and explore the latest sequencing technologies.
• PhD students and graduate researchers studying gene expression and bioinformatics who want hands-on training in RNA-Seq and its applications.
• Biotech professionals working in genomic research, drug discovery, or personalized medicine who want to apply transcriptomic data to their projects.

Job Opportunities

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

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

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:

• Deep understanding of transcriptomic data and its significance in gene expression research.
• Expertise in RNA-Seq library preparation, from RNA extraction to sequencing.
• Hands-on experience with bioinformatics tools for processing and analyzing RNA-Seq data.
• Ability to perform differential gene expression analysis and integrate functional annotation for comprehensive biological insights.
• Career-ready skills in transcriptomic data analysis and bioinformatics.