DNAnexus-Powered Mosaic Microbiome Platform Announces Winners of Second Community Challenge

Teams from the National Center for Biotechnology Information (NCBI) and One Codex score highest in the community challenge focused on advancing computational methods for targeted strain detection.

MOUNTAIN VIEW, Calif.--()--DNAnexus, the global leader in biomedical informatics and data management, today announced the winners of the Mosaic Community Challenge: Clinical Strain Detection, which evaluated the accuracy of microbial strain detection in metagenomic samples. The challenge is the second in a series of three Mosaic Challenges sponsored by Janssen Research & Development, LLC through the Janssen Human Microbiome Institute. The challenges are designed to foster collaboration among academia, industry, and government organizations, and advance innovation in the microbiome field by providing a platform for participants to compare the performance of their tools and protocols with that of others around the world.

Richa Agarwala and Sergey Shiryayev, scientists at the National Center for Biotechnology Information (NCBI), a division of the National Library of Medicine, and a team from One Codex, a leading microbial genomics and metagenomics platform, were co-winners of the challenge, scoring highest for targeted strain detection. Their winning entries correctly identified 39 of the 40 tested microbial strains. Detailed results from the Clinical Strain Detection challenge can be found at: https://platform.mosaicbiome.com/challenges/6.

The Clinical Strain Detection Challenge focused on benchmarking and advancing computational methods for targeted strain detection of known isolates. This challenge differs from the first Mosaic Community Challenge, Strains #1, which aimed at characterizing the microbiome at a high resolution more broadly. Challenge results indicate that in profiling the microbiome, comprehensive microbiome databases and accurate “de-noising” algorithms bring an apparent advantage and minimize false positive identifications. However, in targeted strain detection the precision is driven by the detection algorithm used for mapping data to known isolate genomes. The challenge organizers look forward to digging deeper into the challenge results together with the community to maximize learnings and to continue to drive innovation in this space.

“In order to develop microbial-based products, it is critical to be able to accurately detect microbes at the strain level,” said Richard Daly, Chief Executive Officer of DNAnexus. “Existing computational methods and tools perform well at identifying microbiomes at the species level but fail to do so at the strains level. Through administering this challenge, we hope to advance the precision, resolution, scalability, and usability of computational tools to understand microbes, and unlock the potential of the microbiome.”

“One Codex is excited to have participated in the Mosaic Clinical Strain Detection Challenge and believes that benchmarking and community standards play a critical role in advancing microbiome research,” said Nick Greenfield, the CEO of One Codex. “For us, this Challenge also served to demonstrate the power of next-generation sequencing for evaluating and tracking strains across microbiome datasets, and hints at the insights such approaches may unlock within the field. One Codex is excited that it will soon be able to bring these capabilities to all of its users in both preclinical research and the broader academic community.”

Richa Agarwala at the NCBI commented that her team was “very pleased to take part in the challenge, as it enabled us to learn more about the current state of the metagenomic sequencing and analysis tools that the microbiome community is interested in developing.” She added that, “it is very gratifying to engage in work that aims to help advance this rapidly evolving area of science.”

Launched in collaboration with Janssen Research & Development, LLC, Mosaic serves as an open and inclusive community to accelerate the advancement of microbiome research. The cloud-based Mosaic microbiome platform, powered by DNAnexus, provides a secure environment for scientists to collaborate on research, share data, and advance methods aimed at increasing understanding of the human microbiome, while accelerating the translation of these insights into healthcare solutions.

The third Mosaic Community Challenge, Standards, is open now through Spring 2019, and aims to advance the understanding of the role of protocols in the reproducibility and comparability of results across studies, a key gap in translating innovation to the clinic. Challenge participants will receive a diverse sample set for analysis. Samples are provided free of charge to maximize the number of labs around the world that can join this challenge and compare their data generation pipelines, protocols, and more on the computational platform Mosaic.

Winners of the Clinical Strain Detection Challenge will present on their methods during a DNAnexus webinar on October 10th at 10:00 a.m. PT (1:00 p.m. ET). Registration is free at: https://dnanexus.zoom.us/webinar/register/WN_hM3xZ_29S4Kh3prVBcfjMQ.

About DNAnexus

DNAnexus, the global leader in biomedical informatics and data management, has created the global network for genomics and other biomedical data, operating in North America, Europe, Asia-Pacific (including China), South America, and Africa. The secure, scalable, and collaborative DNAnexus Platform helps thousands of researchers across a spectrum of industries – biopharmaceutical, bioagricultural, sequencing services, clinical diagnostics, government, and research consortia – accelerate their genomics programs globally. For more information on DNAnexus, please visit www.dnanexus.com or follow the company @DNAnexus.

Contacts

Media Contacts:
CG Life for DNAnexus
Mark Button, 408-310-2168
mbutton@cglife.com
or
Alyssa Salela, 630-935-6369
asalela@cglife.com

Contacts

Media Contacts:
CG Life for DNAnexus
Mark Button, 408-310-2168
mbutton@cglife.com
or
Alyssa Salela, 630-935-6369
asalela@cglife.com