Today at the Advances in Genome Biology & Technology (AGBT) conference, we are excited to unveil the largest searchable database of microbial genomes. Curated from its larger collection of hundreds of thousands of genomes, the latest One Codex Database includes >80,000 genomes and provides unprecedented sensitivity and specificity for metagenomic applications.

The latest One Codex Database enables:

• Highly sensitive identification of microbes in complex samples
• Precise quantification of microbial abundances from whole genome sequencing (WGS) data
• Community-wide characterization of complex microbial samples, including the human microbiome

Spanning the tree of life

Our latest release includes over 80,000 genomes, representing more than 43,000 distinct species and 69,000 strains across all microbial domains. We’ve increased coverage of all branches of the tree of life, with nearly 1,700 fungal genomes, another 1,700 archaeal genomes, 27,000 viruses, and more than 53,000 bacteria. Collectively, this database provides the most comprehensive snapshot of complex microbial samples.

Today, we’re extremely excited to announce several new features we’ve been working on for the past few months. Collectively, these should make it both easier and faster to perform custom, large-scale analyses, explore your data, and build applications atop the One Codex platform:

• A new easier-to-use, more powerful API (read the docs)
• A new version of our command-line interface and an accompanying Python client library for quickly getting started with the new API (take a peek on Github)
• And last but not least – interactive notebooks built directly into the platform!

The new Notebooks feature allows you to launch secure Jupyter (née IPython) notebooks automatically configured for access to your samples and analyses on One Codex. Internally, we’ve already found these incredibly useful for both quick, flexible explorations of metagenomic data as well as more sophisticated, formal analyses.

Today we’d like to tell you about a new feature on One Codex that allows you to run new analyses against your samples, including AMR gene panels and whole-genome alignments.

Running New Analyses

When samples are uploaded to One Codex, we automatically classify them using the One Codex Database of ~40K complete microbial genomes. However, metagenomic classification is just one of a range of microbial analysis tools provided by the One Codex platform. While in the past we’ve configured additional analyses to run automatically where appropriate (e.g., MLST for common bacterial isolates) or at the request of users, our new Run Analysis page allows you to run an in silico panel or perform whole-genome alignments against any of your samples.

Today we’re excited to announce a major update to One Codex, which includes both improvements to our core metagenomics pipeline and an expansion of our reference database. Along with this update, we’ve also re-analyzed all samples previously uploaded to One Codex (all older analyses of course remain available).

Improved classifier: Better filtering, while maintaining sensitivity

Over the past few years, a number of new k-mer based metagenomic classifiers tools have been developed, including Kraken, GOTTCHA, CLARK, and our own. These methods have enabled ever-larger reference libraries and provided extremely sensitive detection. As a consequence of their design, however, they have also been more prone to false positives than more conservative alignment- or marker-based approaches.

Today is a big day for One Codex, where we’re launching out of beta!

This marks the introduction of a number of new features (and many under-the-hood improvements), and incorporates much of the feedback our users have provided this year. You will notice some changes to our website, and the platform can now be found at app.onecodex.com (note that all previous links to the beta site will still work).

We’re excited to announce that the CDC’s Advanced Molecular Detection initiative has named One Codex as the winner of its $200K “No-Petri-Dish” Challenge! We are thrilled to be recognized by a world-leading public health agency and excited to begin offering solutions for next-generation public health and epidemiology.

The “No-Petri-Dish” Diagnostic Test Challenge asked participants to develop a fast “straight-to-strain” method for identifying a type of E. coli known as STEC (a common cause of severe foodborne outbreaks). Current tests available to public health officials fall into two major categories: “culture-based” tests, which require growing a bacterial culture and can take days or weeks to complete; and faster, but significantly less informative tests for specific pathogens or toxins (e.g., PCR-based tests).