CSHL Tutorials in Genomics & Bioinformatics: RNA-Seq Analysis Course, Apr 28-30

  • SorghumBase Team
  • 19 February 2024

Cold Spring Harbor Laboratory is hosting a course, “Tutorials in Genomics & Bioinformatics: RNA-Seq Analysis,” an intensive two-day introductory course to genomics and  bioinformatics, from April 28-30, 2024. The course is broken into modules that are each designed to give a broad overview of a given topic; a brief lecture describing the theory, methods and tools is followed by a set of worked examples that students complete. Students have opportunities to ask the instructors about tasks or problems they have encountered in their research. Students will be afforded hands-on experience by re-analyzing a published bulk RNA-Sequencing data, featuring resources and examples that primarily come from mammalian species, but are applicable to any species with a reference genome assembly. 

Topics include:

Designing RNA-Seq Studies

  • Best practices in the design of bulk RNA-Seq studies. 
  • Caveats in analysis workflows 

Analysis of High-Throughput Sequence Data Using Galaxy 

  • Importing FASTQ files 
  • Importing reference genomes and annotation
  • Read quality control and diagnostics
  • Read trimming
  • Read mapping and read count estimation

Introduction to R

  • Basic Syntax
  • Data Structures
  • Reading input and writing input
  • Plotting basics

Analysis of RNA-Seq Read Counts using R/DESeq2

  • Diagnostic analyses
  • Normalization
  • Model fitting
  • Testing for differentially expressed genes
  • Data visualization (heatmaps, volcano plots)

Genome Browser Resources

  • Genome annotation
  • Functional genome data
  • Bulk Genome analysis

Gene Set Enrichment and Pathway Analysis

  • Gene set enrichment analysis using Gene Ontology and pathway annotations

Although the course is open to all on a first-come, first-served basis, it is most beneficial for bench scientists transitioning into projects that require intensive analysis or integration of large data sets. It is not appropriate for those with significant programming or data analysis experience.

The class is currently full, but prospective students can register for the waitlist. For more information see the course website.