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基于独特进化枝特异性标记基因的宏基因组微生物群落分析。

Metagenomic microbial community profiling using unique clade-specific marker genes.

机构信息

Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA.

出版信息

Nat Methods. 2012 Jun 10;9(8):811-4. doi: 10.1038/nmeth.2066.


DOI:10.1038/nmeth.2066
PMID:22688413
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3443552/
Abstract

Metagenomic shotgun sequencing data can identify microbes populating a microbial community and their proportions, but existing taxonomic profiling methods are inefficient for increasingly large data sets. We present an approach that uses clade-specific marker genes to unambiguously assign reads to microbial clades more accurately and >50× faster than current approaches. We validated our metagenomic phylogenetic analysis tool, MetaPhlAn, on terabases of short reads and provide the largest metagenomic profiling to date of the human gut. It can be accessed at http://huttenhower.sph.harvard.edu/metaphlan/.

摘要

宏基因组鸟枪法测序数据可以识别微生物群落中的微生物及其比例,但现有的分类分析方法对于越来越大的数据集效率不高。我们提出了一种方法,该方法使用特定进化枝的标记基因,比当前方法更准确、快 50 倍以上地将读取分配到微生物进化枝。我们在兆兆字节的短读序列上验证了我们的宏基因组系统发育分析工具 MetaPhlAn,并提供了迄今为止最大的人类肠道宏基因组分析。可在 http://huttenhower.sph.harvard.edu/metaphlan/ 访问。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53dc/3443552/a21adb902055/nihms397911f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53dc/3443552/ba68fe96544a/nihms397911f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53dc/3443552/2597ffdc0d40/nihms397911f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53dc/3443552/a21adb902055/nihms397911f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53dc/3443552/ba68fe96544a/nihms397911f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53dc/3443552/2597ffdc0d40/nihms397911f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53dc/3443552/a21adb902055/nihms397911f3.jpg

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本文引用的文献

[1]
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PLoS One. 2011-9-12

[2]
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[3]
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Genome Res. 2011-6-20

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Nucleic Acids Res. 2011-5-17

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Nat Methods. 2011-5

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Nat Methods. 2011-3

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Microbial metatranscriptomics in a permanent marine oxygen minimum zone.

Environ Microbiol. 2011-1-7

[10]
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Bioinformatics. 2010-12-1

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