Microbial 'omics

Others on anvi'o

Table of Contents

This page contains testimonials from anvi’o users. We are eternally thankful for their interest and effort. If you think anvi’o has been useful for your journey in microbial ‘omics, please consider sharing your experience with others by sending an e-mail.

Nastassia Patin

I am a postdoc at Georgia Tech studying marine microbial communities, both free-living and host-associated. I have used anvi’o to overlay multiple data sets, including metagenomes and metatranscriptomes. I’ve also used the pangenomics pipeline to compare metagenomic bins with isolate whole genomes. As a relative newcomer to bioinformatics, the strong visualization component of anvi’o helped me understand what the tools “under the hood” were doing and how metagenomic bins can be evaluated. It’s rare to have such a combination of biological and coding expertise, and the combination makes anvi’o truly shine. The extremely comprehensive website and tutorials have been invaluable and really stand out among the plethora of pipeline manuals, websites, and instructions, most of which are sparse at best and downright confusing at worst. And of course, the responsiveness of the anvi’o developer team has made the entire process a joy! I really appreciate the obvious desire to be a source of help to the science community. Keep up the tremendous work, MerenLab!

Mike Lee

I’m a grad student at University of Southern California that uses the tools of bioinformatics to study microbial ecology in lots of different environments. I’ve used anvi’o in some respect for almost every project i’ve worked on since I came across it about 2 years ago. Probably what I’ve found most pragmatically useful has been the process of real-time exploration and manual curation of metagenomic datasets. This has been a huge help to me both in complex environmental metagenomes and when trying to bin out target cultivar genomes from laboratory enrichment cultures. But a very close second for me would be the ability to visualize and manipulate a lot of various data easily. If anvi’o were simply a closed-off blackbox it would still be valuable to me, but where I think it really shines is in its flexibility. One of my favorite parts about the actual writing part of science is trying to find the best way to visualize and present data. With anvi’o I’ve found myself coming up with countless ways to integrate metrics such as expression levels or methylation levels with environmental, correlative, and other data across multiple samples for entire genomes, contigs, or even at the gene level. The unique perspectives these combined visualizations provide have more than once led to realizations and hypotheses that I’m pretty certain I would have missed without good ‘ol pattern recognition. With just a few data tables and anvi-interactive in –manual mode, it’s almost always the wonderful case that the limiting factor is my own creativity. And if ever it’s not, the anvi’o team is excited to be able to expand its capabilities based on how the community wants to use it. They seem to actually care about helping us answer our questions. Thank you for that!

Luke McKay

I am a postdoctoral fellow with the NASA Astrobiology Institute at Montana State University and I investigate novel methane cycling archaea and their potential roles in early evolution. I use Anvi’o to examine metagenomes from hot springs in Yellowstone National Park where we are discovering a variety of previously unknown methane cycling archaea. Typically, I bin with nucleotide word frequency alone but afterwards examine and refine the bins based on coverage in Anvi’o. This allows me to identify core genomes (in high coverage) that are shared by functional variants (in low coverage). I have many favorite aspects of Anvi’o, including the “inspect” feature for individual contigs that lets you run BLAST searches with a single click, the new “concatenate” feature for anvi-get-sequences-for-hmm-hits which allows quick and easy phylogenomic assessments, and finally the immediate calculations of completeness and redundancy while manually binning with Anvi’o. It really is incredible to see this information in real time so that I’m not shooting in the dark when I make decisions about bin selection. Anyway, thanks Anvi’o!

Joe Vineis

I am a PhD student at Northeastern University studying microbial communities of salt marsh sediments. Anvi’o is the most important tool in my bioinformatic arsenal because it provides unique visualization and analysis of single cell genomics, metagenomics, transcriptomics, small eukaryotic genomes, and functional/marker gene amplicons. As a microbial ecologist, the ability to reconstruct draft genomes from shotgun metagenomic sequences provides access to the expansive diversity of microbial genomes. While many tools exist to organize sequences into metagenomic assembled draft genomes (MAGs), none provide the visual inspection and data integration capabilities of Anvi’o. The high-resolution images and interactive capabilities provide me the ability to evaluate the accuracy of binning methods which is of utmost importance when recovering draft genomes from metagenomic data. As the number of metagenomic assembled genomes continues to grow in public databases, Anvi’o will be an important tool that allows the research community to quickly evaluate these genomes and integrate them into their own work. I recently started a large project involving over 16,000 MAG and cultivar genomes. Anvi’o provides a wonderful foundation to create a database for these genomes that will store all relevant metadata and allow for streamlined query of functions, sequences, and the ability to extend into pangenomic and phylogenomic analyses. The flexibility of the platform results in a playground where there are few obstacles to important biological discovery. Excellent tutorials and a team of developers dedicated to meeting the needs of the scientific community make Anvi’o my choice for all ‘omics analyses. To date, I have used Anvi’o to recover MAGs, identify potential gene conversion events in a rotifer genome, track expression of genes mobilized by a conjugative transposon, identify bacterial contaminants in a eukaryotic genome, and explore environmental variation and phylogenetic organization of bacterial functional genes. Thank you Anvi’o!

Rika Anderson

I am an Assistant Professor at Carleton College interested in microbial ecology and evolution in deep-sea hydrothermal vents. I use anvi’o for recovering and curating metagenome-assembled genomes (MAGs), as well as identifying and analyzing single nucleotide variants (SNVs) in those MAGs. I am deeply appreciative of the flexibility provided by anvi’o, the relative ease of visualizing, comparing and exploring multiple datasets, the comprehensive documentation, and the responsiveness of the developers. I’ve also been using it in education for my undergraduate level Genomics and Bioinformatics class as an intuitive way to create and visualize metagenomic bins. The interactive interface gives my students an intuitive way to explore the data and make impressive figures, while at the same time the entire software package gives them practice with using the command line. Thanks for all of your hard work on this!

Damien Courtine

I am a PhD student at the University of Western Brittany (UBO), France, interested in understanding the formation of new species in deep-sea hydrothermal vents. I use anvi’o mainly for its pangenomics pipeline. It is easy to find groups of proteins unique or shared across species/genomes/environments, etc. In addition, anvi’o provide the list of single-copy core genes, really useful to build a robust phylogenies! The layers of metadata is very powerful, especially to order samples according to their origin or whatever you want!

I use anvi’o is to quickly visualize a genome/sample. I had a problem with one strain, the assemblers could not output a small number of contigs. With anti-interactive + a blank profile (from anvi-profile), I inspected this sample and I found 2 different genomes thanks to the completeness and redundancy.

I did a last thing with anvi’o: with a bunch of deep-sea metagenomes, I visualized where and what percentage of the my genomes are detected in each metagenome.

To finish, you find a bug / have any question? Share it through GitHub/Google groups, the anvi’o team answer as fast as possible!

For me, it is a great pleasure to work with anvi’o, so thank you Meren Lab!