Dahak Metagenomics¶

Dahak Metagenomics is a project to build workflows for non-clinical metagenomic analyses.

Find the dahak-metagenomics organization on Github at https://github.com-metagenomics.

Dahak¶

Dahak is a software suite that integrates state-of-the-art open source tools for metagenomic analyses. Tools in the dahak software suite will perform various steps in metagenomic analysis workflows including data pre-processing, metagenome assembly, taxonomic and functional classification, genome binning, and gene assignment. We aim to deliver the analytical framework as a robust and reliable containerized workflow system, which will be free from dependency, installation, and execution problems typically associated with other open-source bioinformatics solutions. This will maximize the transparency, data provenance (i.e., the process of tracing the origins of data and its movement through the workflow), and reproducibility.

Find the dahak repository on Github at https://github.com/dahak-metagenomics/dahak.

Getting Started¶

Analysis protocols can be found in the workflows directory. It is assumed that analysis will begin with read filtering and instructions for Docker installation are included there.

You can run these protocols interactively using Docker or automate them using Snakemake and Singularity. See the workflows README for Docker, Snakemake and, Singularity install instructions.

The assembly, comparison, functional inference, and taxonomic classification workflows are dependent upon the output of the read filtering workflow data. You can download our data to use in the read filtering protocol from the Open Science Framework (OSF). See the section below titled Data and the read filtering protocol for more information.

Prerequisites¶

Currently, for the sake of simplicity, it is assumed that all workflow steps will be run from Ubuntu 16.04 LTS.

dahak is not a standalone program, but rather a collection of workflows that are defined in snakemake files and that utilize bioconda and Docker to install and run software for different tasks.

See the workflows/ directory to get started.

Data¶

For purposes of benchmarking this project will use the following datasets:

Dataset	Description
Shakya complete	Complete metagenomic dataset from Shakya et al., 2013^* containing bacterial and archaeal genomes
Shakya subset 50	50 percent of the reads from Shakya complete
Shakya subset 25	25 percent of the reads from Shakya complete
Shakya subset 10	10 percent of the reads from Shakya complete

^*Shakya, M., C. Quince, J. H. Campbell, Z. K. Yang, C. W. Schadt and M. Podar (2013). "Comparative metagenomic and rRNA microbial diversity characterization using archaeal and bacterial synthetic communities." Environ Microbiol 15(6): 1882-1899.

Contributing¶

Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests to us.

Contributors¶

Phillip Brooks¹, Charles Reid¹, Bruce Budowle², Chris Grahlmann³, Stephanie L. Guertin³, F. Curtis Hewitt³, Alexander F. Koeppel⁴, Oana I. Lungu³, Krista L. Ternus³, Stephen D. Turner^4,⁵, C. Titus Brown¹

¹School of Veterinary Medicine, University of California Davis, Davis, CA, United States of America

²Institute of Applied Genetics, Department of Molecular and Medical Genetics, University of North Texas Health Science Center, Fort Worth, Texas, United States of America

³Signature Science, LLC, Austin, Texas, United States of America

⁴Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States of America

⁵Bioinformatics Core, University of Virginia School of Medicine, Charlottesville, VA, United States of America

See also the list of contributors who participated in this project.

License¶

This project is licensed under the BSD 3-Clause License - see the LICENSE file for details.

Acknowledgments¶

Bioconda
Hat tip to anyone whose code was used