Today we’re happy to announce two new features for all users on One Codex: whole genome clustering and integration with Illumina’s BaseSpace. The first opens the door to new types of analyses, while we hope the second will allow many to spend less time moving their data around and more time exploring it! Whole (meta)genome clustering In addition to our previous sample comparison tool, we’re very excited to announce that One Codex now supports arbitrary, interactive exploration and clustering of your isolates and metagenomic samples.
Ok, anthrax might sound a bit scary, but this is a story about something that should make you feel good. Wait, is that really Anthrax? Back in the Spring of 2015, researchers studying the microbial ecology of the built environment generated a very large amount of genomic data from microbes found in the New York City subway system. To give you some idea of the magnitude, they generated 10.4 billion sequence reads across 1,457 samples.
Today we added automated Multi-Locus Sequence Typing (MLST) to One Codex. MLST is a powerful epidemiological tool that is based on curated collections of conserved mutations in core marker genes. This common reference standard is used to differentiate closely-related isolates of the same species, with many common species having hundreds or thousands of defined MLST profiles. Datasets that are identified as being isolates or single-genome assemblies will be automatically analyzed and tagged with the detected ST label.
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).
Today we’re launching our new sample comparison tool on the One Codex Beta Platform. The tool enables quick selection and comparison of any of your samples and displays the abundance of taxonomic groups in each sample as a stacked bar graph: The comparison view supports large side-by-side comparisons, viewing data at a particular taxonomic level and/or abundance, filtering to specific clades, and relative vs. absolute scaling modes. See an example and try out the tool here