Contributed Talk 2: The Initiative for the Critical Assessment of Metagenome Interpretation (CAMI)
Duration: 12 mins 54 secs
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| Description: |
McHardy, AC (HHU Düsseldorf, Germany)
Thursday 11 September 2014, 10:40-10:55 |
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| Created: | 2014-09-15 14:02 |
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| Collection: | Understanding Microbial Communities; Function, Structure and Dynamics |
| Publisher: | Isaac Newton Institute |
| Copyright: | McHardy, AC |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
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| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | Co-author: Alexander Sczyrba, Eddy Rubin, Nikos Kyrpides, Paul Schulze-Lefert, Julia Vorholt, Nicole Shapiro, Tanja Woyke, Hans-Peter Klenk, Stephan Majda, Johannes Droege, Ivan Gregor, Peter Hofmann, Eik Dahms, Jessika Fiedler, Ruben Garrido-Oter, Yang Bai, Girish Srinivas, Phil Blood, Mihai Pop, Aaron Darling, Matthew DeMaere, Dmitri Turaev, Chris Hill, Peter Belmann, Andreas Bremges, Thomas Rattei ()
In just over a decade, metagenomics has developed into a powerful and productive method in microbiology and microbial ecology. The ability to retrieve and organize bits and pieces of genomic DNA from any natural context has opened a window into the vast universe of uncultivated microbes. Tremendous progress has been made in computational approaches to interpret this sequence data but none can completely recover the complex information encoded in metagenomes. A number of challenges stand in the way. Simplifying assumptions are needed and lead to strong limitations and potential inaccuracies in practice. Critically, methodological improvements are difficult to gauge due to the lack of a general standard for comparison. Developers face a substantial burden to individually evaluate existing approaches, which consumes time and computational resources, and may introduce unintended biases. CAMI (cami-challenge.org) is a new community-led initiative designed to tackle these problems by aiming for an independent, comprehensive and bias-free evaluation of methods. We are making extensive high-quality unpublished metagenomic data sets available for developers to test their short read assembly, binning and taxonomic classification methods. The results of CAMI will provide exhaustive quantitative metrics on tool performance to serve as a guide to users under different scenarios, and to help developers identify promising directions for future work. As a community effort, we encourage feedback by both method developers and users of metagenome analysis tools. We urge developers to already register for the competition on our website and to join our Google+ group to provide feedback on the current design phase. The competition is tentatively scheduled to open at the end of 2014. The results will be presented and discussed in a workshop after the competition. We aim for a publication of the generated insights together with all CAMI contest participants and data contributors. |
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