Introduction

This intensive 25-hour training is designed to take you from raw RNA-seq data to biological interpretation using standard bioinformatics workflows.

Program Details

• Dates: June 8th to June 12th (08/06 – 12/06)
• Schedule: 9:00h to 14:00h CEST daily
• Format: 100% Online (Virtual Classroom)
• Course Duration: 25 Hours
• Computational Intensity: 50% Hands-on Training
• Certification: An official Attendance Certificate is provided upon completion.
• Audience: PhD students, researchers, and companies interested in performing RNA-seq experiments.

The curriculum begins with foundational Linux command-line skills, teaching students how to manage files on servers, install software, and execute bioinformatics pipelines. Participants will then learn R programming via RStudio, focusing on data manipulation, Bioconductor package management, and data visualization with ggplot2. The course then provides an overview of NGS technologies and their application to transcriptomics studies, covering the fundamentals of RNA-seq experimental design, data quality control, and analysis.

I. Introduction to Linux & Server Management

• Basic Command Line: Navigating directories and file systems.
• Software Management: How to download and install specialized bioinformatics programs.
• Data Logistics: Transferring files (upload/download) to and from remote servers.
• Pipeline Execution: Foundations of running automated bioinformatics workflows.

II. Introduction to R & Bioconductor

• The Environment: Mastering RStudio, the console, and basic syntax.
• Package Management: Navigating the Bioconductor ecosystem and installation protocols.
• Data Structures: Understanding types of variables and how to manipulate biological data frames.
• Data Visualization: Introduction to ggplot2 for publication-quality graphics.

III. Introduction to NGS & RNA-seq Analysis

• Technologies: Overview of NGS (short and long reads) and Illumina sequencing.
• Quality Control: Practical methods for Illumina data QC.
• Experimental Design: Best practices for RNA-seq and transcriptomics studies.
• End-to-End Workflow: From raw reads to differential expression analysis and functional annotation.

Registration & Enrollment Policy

• Minimum Requirements: A high-quality, high-speed internet connection. No prior programming skills are required. Participants are assumed to have a basis in biology, genetics, and molecular biology.
• Enrollment Note: This is a small-group training to ensure high-quality hands-on learning.
  The course will be confirmed once the minimum number of participants is reached. If the minimum enrollment is not met, the course will not proceed and participants will be notified in advance.

Enjoy a 10% discount if you are a SIGA member.

Reservation: Places will be formally reserved after accepting the training’s fee or an official Purchase Order. To apply for a place, please fill out the form below.

For any further inquiries, please contact us.