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QIIME allows analysis of high-throughput community sequencing data

QIIME allows analysis of high-throughput community sequencing data correspond ence line built using the PyCogent toolkit , to address the problem of QIIME allows analysis of high- taking sequencing data from raw sequences to interpretation and database deposition. QIIME, available at http://qiime.sourceforge. throughput community sequencing data net/, supports a wide range of microbial community analyses and To the Editor: High-throughput sequencing is revolutionizing visualizations that have been central to several recent high-pro- microbial ecology studies. Efforts like the Human Microbiome file studies, including network analysis, histograms of within- or 1 2 Projects and the US National Ecological Observatory Network are between-sample diversity and analysis of whether ‘core’ sets of helping us to understand the role of microbial diversity in habitats organisms are consistently represented in certain habitats. QIIME within our own bodies and throughout the planet. also provides graphical displays that allow users to interact with the Pyrosequencing using error-correcting, sample-specific barcodes data. Our implementation is highly modular and makes extensive allows hundreds of communities to be analyzed simultaneously in use of unit testing to ensure the accuracy of results. This modularity multiplex . Integrating information from thousands of samples, allows alternative components for functionalities such as choosing including those obtained from time series, can reveal large-scale http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Nature Methods Springer Journals

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References (28)

Publisher
Springer Journals
Copyright
Copyright © 2010 by Nature Publishing Group
Subject
Life Sciences; Life Sciences, general; Biological Techniques; Biological Microscopy; Biomedical Engineering/Biotechnology; Bioinformatics; Proteomics
ISSN
1548-7091
eISSN
1548-7105
DOI
10.1038/nmeth.f.303
Publisher site
See Article on Publisher Site

Abstract

correspond ence line built using the PyCogent toolkit , to address the problem of QIIME allows analysis of high- taking sequencing data from raw sequences to interpretation and database deposition. QIIME, available at http://qiime.sourceforge. throughput community sequencing data net/, supports a wide range of microbial community analyses and To the Editor: High-throughput sequencing is revolutionizing visualizations that have been central to several recent high-pro- microbial ecology studies. Efforts like the Human Microbiome file studies, including network analysis, histograms of within- or 1 2 Projects and the US National Ecological Observatory Network are between-sample diversity and analysis of whether ‘core’ sets of helping us to understand the role of microbial diversity in habitats organisms are consistently represented in certain habitats. QIIME within our own bodies and throughout the planet. also provides graphical displays that allow users to interact with the Pyrosequencing using error-correcting, sample-specific barcodes data. Our implementation is highly modular and makes extensive allows hundreds of communities to be analyzed simultaneously in use of unit testing to ensure the accuracy of results. This modularity multiplex . Integrating information from thousands of samples, allows alternative components for functionalities such as choosing including those obtained from time series, can reveal large-scale

Journal

Nature MethodsSpringer Journals

Published: Apr 11, 2010

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