RNA-Seq Analysis (RNAA02) – Practical NGS & Transcriptomics Data Analysis
Only 3 places left!
RNA-Seq Analysis (RNAA02)
Delivered by Dr. Frances Turner, a bioinformatician at the University of Edinburgh with extensive experience supporting researchers in the analysis and interpretation of high-throughput sequencing data, including whole-genome, transcriptomic, and metagenomic datasets.
Learn how to analyse bulk RNA-Seq data, taking sequencing data from experimental design and initial quality control through alignment, gene-expression quantification, differential expression, visualisation, and functional interpretation.
RNA-Seq is one of the most widely used next-generation sequencing approaches for investigating gene expression. However, producing biologically meaningful results requires careful decisions at every stage of the analysis, from experimental design and read QC to alignment, quantification, statistical modelling, and interpretation. This course provides hands-on training in a complete RNA-Seq workflow, giving participants the practical skills needed to analyse their own sequencing datasets confidently. What you'll gain
Participants should have basic experience with R, RStudio, and Linux, together with a basic understanding of transcriptomics and molecular biology. Why take this course?
RNA-Seq workflows involve considerably more than simply running differential-expression software. Decisions made during experimental design, QC, alignment, quantification, filtering, statistical modelling, and visualisation can all influence the final biological conclusions.
This course takes participants through the complete bulk RNA-Seq analysis workflow, helping you understand not only how to run the analysis but also how to identify potential problems and make appropriate analytical decisions.
Whether you're comparing treatments, conditions, genotypes, tissues, developmental stages, or other biological groups, you'll gain practical experience using DESeq2 and associated bioinformatics tools to identify, visualise, and functionally interpret differential gene expression. Course dates
21–24 September 2026
18:00–21:30 UK time
14 hours | Live online | £350 Learn more & enrol
PR Stats course page – RNA-Seq Analysis (RNAA02) Questions?
Email: [email protected]
Only 3 places left!
RNA-Seq Analysis (RNAA02)
Delivered by Dr. Frances Turner, a bioinformatician at the University of Edinburgh with extensive experience supporting researchers in the analysis and interpretation of high-throughput sequencing data, including whole-genome, transcriptomic, and metagenomic datasets.
Learn how to analyse bulk RNA-Seq data, taking sequencing data from experimental design and initial quality control through alignment, gene-expression quantification, differential expression, visualisation, and functional interpretation.
RNA-Seq is one of the most widely used next-generation sequencing approaches for investigating gene expression. However, producing biologically meaningful results requires careful decisions at every stage of the analysis, from experimental design and read QC to alignment, quantification, statistical modelling, and interpretation. This course provides hands-on training in a complete RNA-Seq workflow, giving participants the practical skills needed to analyse their own sequencing datasets confidently. What you'll gain
- A strong understanding of RNA-Seq experimental design
- Practical experience assessing raw sequencing data and performing quality control
- Skills in aligning RNA-Seq reads to a reference genome and assessing alignment quality
- Understanding of gene-expression quantification and common analytical pitfalls
- Practical experience performing differential expression analysis with DESeq2
- Skills using PCA to explore sample relationships and variation
- Experience analysing complex experimental designs, covariates, and continuous variables
- Skills visualising differential expression using approaches including volcano plots and MA plots
- Understanding of functional analysis of differential expression using FGSEA
- A reproducible workflow for taking RNA-Seq data from raw reads through to biological interpretation
- 4-day live, instructor-led online course
- 3.5 hours per day
- Hands-on practical exercises throughout
- All required software provided through a browser-accessible virtual machine
- Code, datasets, and presentation materials provided
- All sessions recorded
- 30 days of recording access and post-course email support
- Opportunity to discuss your own RNA-Seq projects and analysis questions
- Bioinformaticians and computational biologists
- Researchers working with bulk RNA-Seq and NGS data
- Genomics and transcriptomics researchers
- Molecular and cell biologists
- PhD students and postgraduate researchers
- Researchers who are planning an RNA-Seq experiment or need to analyse existing sequencing data
Participants should have basic experience with R, RStudio, and Linux, together with a basic understanding of transcriptomics and molecular biology. Why take this course?
RNA-Seq workflows involve considerably more than simply running differential-expression software. Decisions made during experimental design, QC, alignment, quantification, filtering, statistical modelling, and visualisation can all influence the final biological conclusions.
This course takes participants through the complete bulk RNA-Seq analysis workflow, helping you understand not only how to run the analysis but also how to identify potential problems and make appropriate analytical decisions.
Whether you're comparing treatments, conditions, genotypes, tissues, developmental stages, or other biological groups, you'll gain practical experience using DESeq2 and associated bioinformatics tools to identify, visualise, and functionally interpret differential gene expression. Course dates
21–24 September 2026
18:00–21:30 UK time
14 hours | Live online | £350 Learn more & enrol
PR Stats course page – RNA-Seq Analysis (RNAA02) Questions?
Email: [email protected]