One Codex (YC S14) Wins the CDC's “No-Petri Dish” Challenge

Sure -- "next-generation sequencing" (NGS) is a term for a variety of hardware platforms that allow reading the nucleotide sequences of DNA molecules.[1] This genomic data can then be used in a variety of end applications, such as looking for genetic disease markers in humans, identifying and characterizing a bacterial infection (the focus of the CDC's prize), etc. The cost of NGS has fallen dramatically in recent years (and throughout/speed increased), making it pragmatic for more and more applied use cases.

[1] The underlying hardware innovations here are varied and fairly remarkable. We focus on the software and data side, so this is not my area, but Wikipedia has a decent synopsis of current approaches: http://en.m.wikipedia.org/wiki/DNA_sequencing#Next-generatio...

1. We're working from a variety of sample types (those you mentioned) as well as cultured isolates.

2. The technology demonstrated for the CDC prize takes ~20 minutes to process an Illumina HiSeq run. And there's a lot of further optimization opportunity. Put differently, the bioinformatics are sufficiently fast so as to be "real time" (i.e., they could be stream processed off of a sequencer, and don't require a substantial % of additional time over the hardware runtime).

3. In general, the false positive and negative rates for our (bioinformatic/in silico) approach are very good. But, ultimately these rates also depend greatly on the underlying hardware and the sample collection, preparation, etc. protocol.

4. A) Yes, we can identify any strain across a reference library of several thousand E. coli strains. B) Yes, and we're starting with, E. coli, Salmonella, and several others.

5. Yes - but this getting rather long, so pls. e-mail me (below) if you're interested in discussing further.

6. I'm not intimately familiar with the system in question, but in general NGS offers greater "resolution" than other molecular approaches. And, as the existence of this initiative at CDC hints, having this resolution is particularly important for strain-typing and other public health functions. Ultimately, we think many of these benefits will also carry over in the form of better clinical (diagnostic) information and data collection.

Happy to chat about this further if it's of interest. My email is nick@onecodex.com.

Yes, we're principally using a k-mer based approach. Happy to chat further offline. Email is above or in my profile.