(2020) Informatics and Statistics for Metabolomics

Using high-throughput technologies, life science researchers can identify and characterize all the small molecules or metabolites in a given cell, tissue, or organism. The CBW course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Hands-on practical tutorials using various data sets and tools will assist participants in learning metabolomics analysis techniques.

Participants will gain practical experience and skills to be able to:

• Design appropriate metabolome-focused experiments
• Understand the advantages and limitations of metabolomic data analysis
• Devise an appropriate bioinformatics workflow for processing and analyzing metabolomic data
• Apply appropriate statistics to undertake rigorous data analysis
• Visualize datasets to gain intuitive insights into the composition and/or activity of their metabolome

This course is intended for graduate students, post-doctoral fellows, clinical fellows and investigators who are interested in learning about both bioinformatic and cheminformatic tools to analyze and interpret metabolomics data.

You will also require your own laptop computer. Minimum requirements: 1024×768 screen resolution, 1.5GHz CPU, 2GB RAM, 10GB free disk space, recent versions of Windows, Mac OS X or Linux (Most computers purchased in the past 3-4 years likely meet these requirements). If you do not have access to your own computer, please contact support@bioinformatics.ca for other possible options.

This workshop requires participants to complete pre-workshop tasks and readings.