Microbial Community Metagenomics with the bioBakery and Bioconductor

Wednesday, June 6, 2018 - Thursday, June 7, 2018 8:30 AM - 5:30 PM
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Course Description

Microbial ecology is one of many fields that have benefitted greatly from technical advances in DNA sequencing. In particular, low-cost culture-independent sequencing has made metagenomic and metatranscriptomic surveys of microbial communities practical, including bacteria, archaea, viruses, and fungi associated with the human body, other hosts, and the environment. The resulting data have stimulated the development of new computational approaches to meta'omic sequence analysis, including metagenomic assembly, microbial identification, and gene, transcript, and pathway functional profiling.

We will present a high-level introduction to computational metagenomics, highlighting the state-of-the-art in the field as well as outstanding challenges. These include an introduction to the biological goals of typical meta'omic studies and the bioinformatic processes currently available to achieve them. This will briefly summarize the major aspects of metagenomic analysis to be covered here: reference genome-based community composition and functional profiling, along with methods for constructing new genomic references by using de novo assembly. We will discuss the challenges associated with precisely quantifying members of a microbial community and functional analysis of the gene families in a community, the association of those gene families with their source organisms, and the combination of gene families into pathways for metabolic profiling.

Finally, as sequencing technologies deliver more data for the same price, our ability to examine complex microbial communities using sequencing grows. For environmental communities, many fewer reference genomes or transcriptomes are typically available than for human- associated microbes, and the substantial diversity of many communities means that terabases of sequencing may be needed to recover a significant fraction of the community metagenome. We will introduce large-scale de novo assembly, reference free methods for investigating community coverage, and diversity estimation for shotgun sequencing data. We will conclude with an overview of the statistical challenges inherent to analyzing the compositional and count data arising meta'omic studies, and present Bioconductor solutions for simplifying these analyses. The workshop will include standardized protocols for microbial profiling, functional profiling, and metagenome/metatranscriptome assembly with benchmarks and examples.

Course Objectives

By the end of this course, students will be able to:


  1. Understand all stages of meta'omic analysis from raw sequence data handling and quality control to statistical identification of differentially abundant microbes, microbial genes, and gene functions
  2. Perform metagenomic taxonomic profiling with MetaPhlan2
  3. Perform metagenomic and metatranscriptomic functional profiling with HUMAnN2
  4. Generate synthetic microbiome data using SparseDOSSA and perform quality control, visualization, and dimensionality reduction in preparation for downstream analysis
  5. Perform differential abundance analysis, clustering, and visualization in R/Bioconductor


Registrants will be required to bring a personal laptop with R + Anaconda (Python 3) installed. Additional software installations may be necessary and this will be communicated to registrations closer to the dates of instruction.

Recommended Course Reading List

UNIX Tutorial for Beginners: http://www.ee.surrey.ac.uk/Teaching/Unix/ Quick-R: http://www.statmethods.net/


Abubucker S et al.: Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput. Biol. 2012, 8:e1002358


Franzosa EA et al.: Relating the metatranscriptome and metagenome of the human gut. Proc. Natl. Acad. Sci. U. S. A. 2014, 111:E2329–38


Truong DT et al.: MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat. Methods 2015, 12:902–903


Curtis Huttenhower, PhD
Dr. Curtis Huttenhower is an Associate Professor in Biostatistics at the Harvard School of Public Health and an Associate Member at the Broad Institute. He participated extensively in the NIH Human Microbiome Project and co-leads the "HMP2" Center for Characterizing the gut microbial ecosystem in IBD. His lab focuses on computational methods for functional analysis of microbial communities. This includes systems biology reconstructions integrating metagenomic, metatranscriptomic, and other microbial community 'omics, the human microbiome in autoimmune disease such as IBD, and its potential as a diagnostic tool and point of therapeutic intervention.

Levi Waldron, PhD
Levi Waldron completed a PhD at the University of Toronto and a post-doc in the Huttenhower lab at the Harvard Chan School of Public Health, and is an Associate Professor of Biostatistics at the City University of New York School of Public Health at Hunter College. He was teaching Applied Statistics for High-Throughput Biology as a 2015-16 U.S. Fulbright Scholar and visiting professor at the University of Trento, Italy. He is member of the Bioconductor Technical Advisory Board, developer of core Bioconductor infrastructure for multi-omics data analysis, and is part of an effort to sequence the oral microbiome of a representative sample of New York City as part of the NYC-HANES II project.

Course Fee

Registration for this course is $800.00


The registration period has closed for this event.


Wednesday: Hammer LL203; Thursday: Hammer LL204

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