Anvi’o: An advanced analysis and visualization platform for ‘omics data
- Published
- Accepted
- Subject Areas
- Bioinformatics, Biotechnology, Computational Biology, Genomics, Microbiology
- Keywords
- metagenomics, assembly, genome binning, visualization, SNP profiling, metatranscriptomics
- Copyright
- © 2015 Eren et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Anvi’o: An advanced analysis and visualization platform for ‘omics data. PeerJ PrePrints 3:e1275v1 https://doi.org/10.7287/peerj.preprints.1275v1
Abstract
Comprehensive analysis of shotgun metagenomic assemblies have revolutionized molecular microbial ecology, but few microbiologists command the full suite of bioinformatics skills necessary to process, interact, organize and visualize overlapping DNA sequence contigs. Here we introduce anvi’o, an advanced analysis and visualization platform for ‘omics data, and its assembly-based metagenomic workflow. Anvi’o’s interactive interface facilitates the management of contigs and associated metadata for automatic or human-guided identification of genome bins, and their curation. Its extensible visualization approach distills multiple dimensions of information about each contig into a single, intuitive display, offering a dynamic and unified work environment for data exploration, manipulation and reporting. Beyond its easy-to-use interface, the advanced modular architecture of anvi’o as a platform allows users with programming skills to implement and test novel ideas with minimal effort. To demonstrate anvi’o’s capabilities, we re-analyzed a metagenomic time-series data from an infant gut microbiome. Through the anvi’o interface we identified near-complete draft genomes, and explored temporal genomic changes within the abundant microbial populations through de novo characterization of subtle nucleotide variations. We also used anvi’o to re-analyze a collection of datasets from multiple investigators who studied microbial responses to the Deepwater Horizon oil spill. We linked metagenomic, metatranscriptomic, and single-cell genomic data from the water plume, and used the holistic perspective anvi’o provides to identify the draft genome of a previously uncharacterized, active population of Oceanospirillales. We also linked environmental isolates with metagenomes recovered from an oil-contaminated beach, and identified 56 near-complete draft genomes including abundant oil degraders whose functional features suggested an oceanic origin.
Author Comment
This article is submitted to Genome Biology on July 30, 2015.