Bayesian community-wide culture-independent microbial source tracking.

Bayesian community-wide culture-independent microbial source tracking.
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DOI:
10.1038/nmeth.1650
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发表时间:
2011-07-17
期刊:
影响因子:
48
通讯作者:
Kelley, Scott T.
Kelley, Scott T.
中科院分区:
生物学1区
文献类型:
--
作者:
Knights, Dan;Kuczynski, Justin;Charlson, Emily S.;Zaneveld, Jesse;Mozer, Michael C.;Collman, Ronald G.;Bushman, Frederic D.;Knight, Rob;Kelley, Scott T.

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污染是高通量宏基因组研究中的关键问题,但在全面解决方案方面的进展有限。我们提出了SourceTracker,贝叶斯方法来估计一个新的社区,来自一组源环境的比例。我们将SourceTracker应用于新生儿重症监护室(NICU),办公室和分子生物学实验室的新微生物调查,并为未来的测试提供已知污染物的数据库。
Contamination is a critical issue in high-throughput metagenomic studies, yet progress towards a comprehensive solution has been limited. We present SourceTracker, a Bayesian approach to estimating the proportion of a novel community that comes from a set of source environments. We apply SourceTracker to new microbial surveys from neonatal intensive care units (NICUs), offices, and molecular biology laboratories, and provide a database of known contaminants for future testing.
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