Decode the Transcriptome: A Hands-On Galaxy RNA-Seq Workshop
Master Next-Generation Sequencing (NGS) gene expression analysis through no-code bioinformatics workflows on the web-based Galaxy platform. Transform raw sequencing data into publication-ready differential expression biological insights in this practical two-day training.
- 5.0/5
- English
- Starts 10 May 2026
- Updated Sep 2026
About this course
Unlock the full potential of Next-Generation Sequencing (NGS) data with this comprehensive two-day bioinformatics workshop designed for life sciences professionals and researchers. Transcriptomics forms the backbone of modern molecular biology, enabling precise measurement of gene expression across diverse biological conditions. This hands-on course eliminates complex command-line programming barriers by utilizing the accessible, cloud-enabled Galaxy platform for end-to-end RNA-Seq data processing. Participants will gain practical expertise in evaluating raw FASTQ read quality, trimming low-quality sequences, and performing precise genomic alignment with industry-standard tools like HISAT2 and STAR. You will master quantification techniques to extract gene-level counts using FeatureCounts, followed by rigorous differential expression analysis via DESeq2 and EdgeR. Finally, learn how AI-driven bioinformatics tools enhance data interpretation by transforming statistical outputs into intuitive volcano plots and publication-grade heatmaps. Designed for immediate practical application, this course bridges the gap between raw sequencing outputs and actionable biological discovery.
What you will learn
Skills you will gain
Certification
Available
Issued by Dr. OmicsCourse curriculum
1 moduleWhat you need to start
- Basic understanding of molecular biology concepts (DNA, RNA, gene transcription, and gene expression).
- Basic familiarity with computer operations and web browser navigation (no prior coding, R, or Python experience required).
Who this course is for
- Life Science researchers, molecular biologists, and biotechnologists seeking to analyze their own RNA-Seq datasets without coding.
- Bioinformatics students and academicians wanting practical experience with Next-Generation Sequencing (NGS) workflows.
- Computational biology beginners looking to transition from theoretical genomics to hands-on transcriptomics analysis.