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Description of the Course
Environmental genomics is revolutionizing our understanding of microbes from the environment to human health. At its core are new molecular methods called metagenomics to sequence DNA directly from an environment, thus capturing data on the entire microbial community and bypassing culture. Modern (Next-Gen) sequencing technologies produce massive sequence datasets that allow for these new insights, but also present new hurdles in interpreting them. This hands-on course teaches students the biological concepts behind working with genetic data from these complex communities, and practical bioinformatics approaches for analyzing the data. Students work in a collaborative learning classroom to gain skills in (1) beginning Unix and python, (2) bioinformatics techniques for analyzing large-scale metagenomic datasets, and (3) high-performance computing for bioinformatics. These skills are taught by implementing a real-world metagenomics project to understand how genes, pathways, and environmental context can be translated into ecosystem-level knowledge (in the environment or human health).
Course Objectives and Expected Learning Outcome
To develop the broad knowledge and skills needed to: (a) understand metagenomic experimental approaches; (b) implement bioinformatics analyses on metagenomes from complex community samples, and (c) conduct and interpret results from project-based metagenomic analyses.
Topics
Metagenomics experimental approaches; sequencing technologies; platforms and platform specific issues; methodologies; sample preparation; QC-reports & quality controls; mapping sequence reads; taxonomic annotation; functional annotation & determination; gene prediction; comparative metagenomics; amplicon sequencing; shotgun sequencing; metagenome assembly; visualization and reporting of results; tools & algorithms; bioinformatics tools.