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RNA-Seq with Galaxy

Learn at your pace [Online Course]

Learn RNA-Seq differential expression analysis to identify genes that are diffentially expressed among different diseases or conditions.

~ 3 Hours

22 Videos

20 Exercises

90 Learners

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Key facts

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No prior Bioinformatics or coding experience required

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For beginners and advanced learners alike

Course Description

  • RNA-Seq is an exciting and in-demand next-generation sequencing (NGS) method used for identifying genes and pathways underlying particular diseases or conditions.

  • As high-throughput sequencing becomes more affordable and accessible to a wider community of researchers, the knowledge to analyze this data is becoming an increasingly valuable skill, especially for those who are still in Bachelors, Masters or even Doctoral degrees.

  • Get yourself enrolled in this in-demand course and learn industrial level RNA-seq workflow and analysis, leading to skills in discovering differentially expressed genes and biological processes which might be important for your condition of interest!

  • The course starts from the very basics of Next Generation Sequencing, the basics of sequencing and how the raw data is produced, then a detailed overall overview is given of the RNA-Seq workflow with an emphasis on differential expression (DE) analysis.

  • The course further covers; how to prepare data for RNA-seq analysis, do quality control and trimming, process the data for mapping against the reference genome, leading to quantification of raw reads for each gene, assess the quality of the count data, and identify outliers and detect major sources of variation in the data.

  • Finally, you will learn how to use DESeq2 to model the reads count data using a negative binomial model and test for differentially expressed genes. Visualization of the results with heatmaps and volcano plots will be performed and the significant differentially expressed genes will be identified and saved, ending with Gene Ontology and Pathway Analysis.

Course Content


Introduction to RNA-Seq Theory & Workflow

In this chapter we explore what is NGS, RNA-Seq and what can do with RNA-Seq data and why it is exciting. We learn about the different steps and considerations involved in an RNA-Seq workflow.

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Introduction to Galaxy

Introduction to NGS & RNA-Seq

Detailed RNA-Seq Workflow


Raw Data Processing & Quality Control

In this chapter we explore what are the ways to get RNA-Seq datasets, how to preprocess the raw reads and do quality control and trimming out the bad qualities. 

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Databases for RNA-Seq Datasets

RNA-Seq Dataset Retrieval 

RNA-Seq Dataset Preprocessing

Quality Control & Report Generation



Mapping & Raw Reads Quantification

In this chapter we teach how to do alignment of the reads against reference genome, visualization and evaluation of the alignment.

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Mapping Against Reference Genome

Inspection of the Alignment with IGV

Evaluation of Mapping Results

Read Duplication Levels

Gene Body Coverage

Number of Reads Mapped to Each Chromosome

Reads Distribution Per Feature

Reads Quantification


Finding DEGs with DESeq2 & Functional Analysis

In this chapter we teach how to use DESeq2 package to find differentially expressed genes and how to do functional analysis of the DEGs.

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DESeq2 Overview

Finding DEGs with DESeq2

Extraction of DEGs

Annotation of DEGs

Visualization of DEGs

Gene Ontology Analysis

KEGG Pathways Analysis


Introduction to RNA-Seq, NGS & Galaxy

Quality Control and Trimming

Mapping & Evaluatin of Alignment

Discovering DEGs with DESeq2 

Functional Analysis with Gene Ontology & KEGG Pathways



100% positive reviews 


90 learners


22 Lessons (~ 3 hours)


Online and at your own pace


Available on your phone

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Audio: English


English, Spanish, French, Arabic, Italian

Level: Basics to Advanced

Commencement of Course: as soon as you have paid!
(Netflix-style Streaming, Complete the course anytime! 1 Year Access)

A real-life project-based hands-on course on RNA-Seq Analysis


What do other learners have to say?


BioCode have helped me a lot to be an international researcher.
Thank you for the opportunity, time and dedication at any time for 3 months!

Ergi Hoxha

Faculty of Natural Sciences


I have been taking BioCode lectures for a few months now and I think it is the best platform to start with understanding the basics to the complexity of Bioinformatics and Computational biology. I highly regard the BioCode team as they are very cooperative and exceptionally helping people and always try to make things easy for you.

Faiza Munir

Drug Discovery


I am currently enrolled in one of the workshops of BioCode and I am enjoying this course a lot. Although, I have no knowledge about proteins and bioinformatics I am learning a lot because the way it is explained is very good. On the other hand, I really appreciate the communication I have been having with the staff members. Although this is a virtual communication it is easy to notice that they are very supportive, respectful and collaborative, so that I am very happy of this choice. I am going to follow another course here and I suggest this to anyone interested to learn more and want to gain very good skills in several issues related to bioinformatics.

Inva Kociaj

University of Tirana

  • You don't need any prior Bioinformatics, programming knowledge or skills for this course, we'll take care of that and teach you the required topics!

  • This course is for both beginners and professionals alike, anyone with biology background can avail this course.

Target Audience

The target audience for this course are biologists, beginner or intermediate Bioinformaticians or data analysts with no or little experience in applications of computational bioinformatics and bioinformatics pipelines for protein analysis.


However, a superficial understanding of molecular biology is expected from you before you join the course.

This hands-on guide will help you properly to understand and perform RNA-seq analysis, and it is quite easy to get started in, even if you lack a proper understanding of the underlying concepts of Bioinformatics databases, servers, tools and the algorithms working behind them.

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