Analysis of Metagenomic Data
Metagenomics, the sequencing of DNA directly from a sample without first culturing and isolating the organisms, has become the principal tool of “meta-omic” analysis. It can be used to explore the diversity, function, and ecology of microbial communities. The CBW has developed a 3-day course providing an introduction to metagenomic data analysis followed by hands-on practical tutorials demonstrating the use of metagenome analysis tools. The tutorials are designed as self-contained units that include example data and detailed instructions for installation of all required bioinformatics tools.
Participants will gain practical experience and skills to be able to:
- Design appropriate microbiome-focused experiments
- Understand the advantages and limitations of metagenomic data analysis
- Devise an appropriate bioinformatics workflow for processing and analyzing metagenomic sequence data (marker-gene, shotgun metagenomic, and metatranscriptomic data)
- Apply appropriate statistics to undertake rigorous data analysis
- Visualize datasets to gain intuitive insights into the composition and/or activity of their data set
Graduates, postgraduates, staff bioinformaticians and PIs working with or about to embark on analysis of marker genes, metagenomic, and metatranscriptomic data from microbiome-focused experiments.
Prerequisites: Basic familiarity with Linux environment and statistical analysis is required. Must be able to complete and understand the following simple Linux tutorial before attending:
You will also require your own laptop computer. Minimum requirements: 1024x768 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, you may loan one from the CBW. Send us an email for more information.
Pre-work and pre-readings can be found on the student workshop pages.
Module 1: Introduction to Metagenomics (Will Hsiao)
Module 2: Marker Gene-based Analysis of Taxonomic Composition (Will Hsiao)
Module 3: Introduction to PICRUSt (Morgan Langille)
Module 4: Metagenomic Taxonomic and Functional Composition (Morgan Langille)
Module 5: Metagenome Assembly, Binning, and Extracting Genomes from Metagenomes (Laura Hug)
Module 6: Metatranscriptomics (John Parkinson)
Module 7: Statistical Tests for Metagenomics (Robert Beiko)
Module 8: Biomarker selection (Fiona Brinkman)