RNA-Seq Analysis RNA-Seq analysis training – live online course covering experiment design, data QC, alignment, gene expression, DESeq2 differential expression, PCA, visualisation, and functional analysis.
*ONLY 5 PLACES LEFT!* https://prstats.org/course/rna-seq-analysis-rnaa01/ Join our four-day live online workshop: *RNA-Seq Analysis (RNAA01)*. If you’re working with RNA-Seq or planning to generate bulk transcriptome data, and you want to take your analysis from raw reads through to biological insight, this is the course for you. *What you will learn* - How to design a robust RNA-Seq experiment and avoid common pitfalls. - How to perform quality control on raw RNA-Seq data, align reads, and assess alignment quality. - How to quantify gene expression and apply the widely-used DESeq2 workflow for differential expression analysis. - How to visualise high-throughput data using principal component analysis (PCA), volcano plots, MA plots and other techniques. - How to perform functional interpretation of differential expression results, turning numbers into biological insight. *Who should attend* - Researchers, postgraduate students and industry professionals working with bulk RNA-Seq data. - Anyone who has basic experience with R, RStudio and the fundamentals of molecular biology or transcriptomics. - Those who want to move from raw sequence data to actionable biological conclusions with confidence. *Course format* - Four days of live online sessions (approximately 3½ hours each day) in a UK / Western European time zone. - Interactive lectures, hands-on practical exercises and dedicated discussion time. - Course materials, code and datasets will be provided, and participants are encouraged to bring their own data for discussion when possible. - Recordings of sessions available after each day for participants across different time zones. *Why this course stands out* - It offers an end-to-end workflow from design through QC, alignment, differential expression and functional analysis — designed specifically for researchers working in transcriptomics. - It emphasises not just how to run the tools, but how to interpret results, understand the assumptions and recognise where things can go wrong. - Designed by experienced bioinformaticians, the course balances theory, practice and discussion in an accessible live-online format. *How to register / next steps* Visit the PR Stats website for full course details, upcoming dates and registration information. Early registration is advisable, as places may be limited. For any questions about suitability, prerequisites or logistics, please contact the course organisers. https://prstats.org/course/rna-seq-analysis-rnaa01/ -- Oliver Hooker PhD. PR stats [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
