Tutorials in Genomics & Bioinformatics: RNA-Seq Analysis
November 10 - 12, 2024

Instructors:

Delphine Fagegaltier, Merck
Emily Hodges, Vanderbilt University School of Medicine
Benjamin King, University of Maine
Steven Munger, The Jackson Laboratory

Tutorials in Genomics & Bioinformatics: RNA Seq is an intensive two-day introductory course to genomics and  bioinformatics. Participants are expected to arrive by 6 p.m. on the first day (Sunday, November 10th)  with the course running two full days until 5 p.m. on the third day (Tuesday, November 12th).

Tutorials in Genomics & Bioinformatics (TGB) is modeled on Cold Spring Harbor Laboratory's  The Genome Access Course, a two day course normally offered in person at CSHL and other locations. TGB is broken into modules that are each designed to give a broad overview of a given topic, with ample time for examples chosen by the instructors. Each module features a brief lecture describing the theory, methods and tools followed by a set of worked examples that students complete. Ample opportunities will be designed for students to engage instructors during the course with specific tasks or problems that pertain to their own research.

The core of the course is the analysis of bulk RNA sequencing. Featured resources and examples primarily come from mammalian species, but concepts can be applied to any species with a reference genome assembly. TGB will provide hands-on experience by re-analyzing a published bulk RNA-Sequencing data set from mammalian tissues.

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

Computers
Each student will be provided with a laptop (if needed) and internet access for the duration of the course. You can also bring your own laptop to the course provided it meets the following requirements: 1) run R and R Studio software (installation instructions will be provided), 2) a standard browser(Chrome, Internet Explorer, Firefox, etc.) that is up-to-date with security patches and bug fixes, 3) wireless internet capacity, and 4) the ability to view and modify plain text files and spreadsheets (e.g., Microsoft Word and Excel). Both PCs and Macs are acceptable as long as they're updated with all security patches and bug fixes.

Target Audience

TGB is open to all on a first-come, first-served registration system. It is most beneficial for bench scientists transitioning into projects that require intensive analysis or integration of large data sets. The course will introduce you to publicly available resources, and it will also help you develop a vocabulary that can be used to collaborate with computational scientists.

If you already have significant programming or data analysis experience, TGB is not appropriate for you. For a more detailed curriculum on methods used in computational biology, please see the Computational Genomics course. Students interested in the practical aspects of software development are encouraged to apply to the course on Programming for Biology. Students who would like in-depth training in the analysis of next-generation sequencing data(e.g., genome assembly and annotation, SNP calling, and the detection of structural variants) may be interested in the course on Advanced Sequencing Technologies. Finally, please see the course on Statistical Methods for Functional Genomics if you would like training in the statistical analysis of high-throughput genomics data.

Support

Limited financial aid is available; please apply in writing to Olivia Mulligan describing your need for financial support.

   

Pricing:
Academic Package (two nights of housing/Single Room/Private Bath): $1,235
Academic Package (two nights of housing/Single Room/Communal Bath): $1,185
Academic Package (two nights of housing/Double Occupancy): $1,105
Corporate Package (two nights of housing/Single Room/Private Bath): $1,960
Academic No-Housing Package: $910
Corporate No-Housing Package: $1,635
Extra nights at $225 per night including food*

*If you are needing to arrive early and/or depart late, please contact Olivia Mulligan for availability and pricing.

All packages cover registration, food, coffee breaks, and a reception. Transportation to and from Cold Spring Harbor is not included. Full payment is due three weeks prior to the course.