Introduction to Omics and Bioinformatics (date TBD)

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.

Virtual Introduction to Python for Bioinformatics (date TBD)

This workshop provides a basic introduction to Python. No prior programming experience is expected or required, however the workshop does move fairly quickly. The workshop is designed to give biologists some fundamental skills to operate in a Linux/Unix environment and to use scripts to manipulate data files and engage in analysis.

Microbiome Analysis Workshop (June 25th-28th, 2024)

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.

Transcriptome Analysis (October 15th-18th, 2024)

This workshop will introduce transcriptome sequencing and analysis techniques. It will include instruction on the use of different analytical tools, relevant file formats, reference genomes, reference-based alignment, and differential gene expression. Bulk, single-cell, and spatial approaches will be covered. The workshop will employ hands-on exercises using complete analytical pipelines on test datasets.

Introduction to R and Data Visualization for Bioinformatics (September 16th-18th, 2024)

This workshop provides a basic introduction to the R language and visualizing data. No prior experience with R or any other programming language is expected or required. This workshop is designed to give biologists fundamental skills for manipulating data and creating visualizations in an R environment with a focus on bioinformatic data.