CSHL Tutorials in Genomics & Bioinformatics: RNA-Seq Analysis course, May 10-12
An Intensive, Hands-On Introduction to Modern Transcriptomics
The Tutorials in Genomics & Bioinformatics: RNA-Seq (TGB) course is a two-day, immersive introduction to genomics and bioinformatics, designed to equip researchers with the conceptual foundation and practical skills needed to analyze high-throughput sequencing data. Modeled after Cold Spring Harbor Laboratory’s renowned Genome Access Course, TGB emphasizes active learning, real data analysis, and direct engagement with expert instructors. This year’s instructors will include:
- Delphine Fagegaltier, Independent Consultant
- Emily Hodges, Vanderbilt University School of Medicine
- Benjamin King, University of Maine
- Vilas Menon, Columbia University Irving Medical Center
- Steven Munger, The Jackson Laboratory
Invited speakers for 2026 will be announced.
This course is particularly well suited for bench scientists who are transitioning into projects involving large-scale sequencing data or who wish to more effectively collaborate with computational researchers. Beyond technical skills, the course helps participants develop the vocabulary and analytical intuition needed to engage confidently in genomics-driven research.
Participants are expected to arrive by 6:00 p.m. on Sunday, May 10, with the course running through Tuesday, May 12 at 5:00 p.m. Over this period, attendees will work through a carefully structured series of modules that combine short lectures with hands-on exercises, reinforcing both theory and application.
The central focus of the course is bulk RNA sequencing analysis. Using a published mammalian RNA-Seq dataset, participants will gain end-to-end experience re-analyzing real experimental data. While examples emphasize mammalian systems, the analytical principles are broadly applicable to any organism with a reference genome.
Key areas of instruction include:
- Designing RNA-Seq Studies: Best practices, experimental considerations, and common pitfalls
- High-Throughput Data Analysis with Galaxy: Importing FASTQ files, reference genomes, and annotations
- Quality Control and Preprocessing: Read diagnostics, trimming, and mapping
- Introduction to R: Core syntax, data structures, input/output, and basic plotting
- Differential Expression Analysis: RNA-Seq read count analysis using DESeq2, including normalization, model fitting, and statistical testing
- Data Visualization: Heatmaps, volcano plots, and diagnostic plots
- Genome Browser Resources: Genome annotation, functional genomics data, and bulk genome analysis
- Gene Set Enrichment and Pathway Analysis: Interpreting results using Gene Ontology and pathway annotations
For more information, visit the course website.
