Education - Training Workshops

Training Workshops Overview

The Institute for Genome Sciences offers regular training courses on 'omics technologies, bioinformatics, and programming. Registration for all 2016 workshops is now open. Please click on the titles below for more information.

IGS Introduction to Genomics and Bioinformatics

This workshop provides an introduction to the methods and tools used in genome analysis. It is designed for attendees who have fundamental knowledge of biology, but no prior genomics experience is expected or required. Topics include sequencing applications/technologies, genome annotation, comparative genomics, transcriptomics, metagenomics. Hands-on exercises using popular bioinformatics tools are included for all topics covered in the course.

IGS Introduction to Programming for Bioinformatics

This workshop provides a basic introduction to three aspects of programming as applied to bioinformatics: Perl, databases, and R. No prior programming experience is expected or required. The workshop is designed to give biologists the fundamental programming tools they need to operate in a Linux/Unix environment and to manipulate data files, engage in analysis, and effectively store and retrieve their data.

IGS Metagenome Analysis Workshop

This workshop will provide attendees with in-depth training on analysis of bacterial community sequence data, both whole metagenome shotgun and 16S. Tools for community profiling, gene clustering, and annotation will be explored. An optional 4th day is included in the workshop for those who elect to bring a dataset of their own for analysis.

IGS Transcriptome Analysis Workshop

This workshop will provide training on the tools used for analysis of RNA-Seq data. Methods covered include: mapping reads to a reference and differential expression analysis.

IGS Prokaryotic Comparative Genomics Workshop

This workshop will explore the tools used for comparisons of multiple (up to dozens) of prokaryotic sequences. Tools for pangenome analysis, whole genome alignment, ortholog clustering, SNP analysis, and visualization of data will be explored.