The One Codex Blog Posts tagged with metagenomics

Announcing SMS-seq: The world’s first protocol for ultra-portable microbial sequencing data analysis and taxonomic identification.

When analyzing microbiome data, it’s very important to know that you are detecting the microbes that are truly present and that the predicted abundances are accurate.¹ However, it can be a lot of work to test and validate microbiome analysis tools across a wide range of conditions. We are very grateful to a group of academic researchers from Weill Cornell Medicine, UC-Riverside, IBM, University of Vermont, HudsonAlpha, & Drexel University who performed those evaluations and contributed them to the community. Today we’re happy to present some results from an independent academic evaluation.² Using the same datasets and accuracy metrics shows the performance of One Codex is superior to a range of other tools for microbiome analysis.

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 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. This cluster view (login/free registration required) enables rapid, reference-free exploration and comparison of NGS samples, often both highlighting expected similarities and revealing important inter-sample differences.

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. That’s a lot of microbiome data.