Evaluating different approaches that test whether microbial communities have the same structure
Evaluating different approaches that test whether microbial communities have the same structure
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DOI：
10.1038/ismej.2008.5
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发表时间：
2008-03-01
期刊：
影响因子：
11
通讯作者：
Schloss, Patrick D.
中科院分区：
文献类型：
--
作者：
Schloss, Patrick D.
随着微生物生态学研究从群落的描述性表征发展到假设驱动的生态学研究，已经开发了许多不同的统计技术来描述和比较微生物群落的结构。到目前为止，这些方法仅使用从微生物群落的不完整表征获得的16 S rRNA基因序列数据进行评估。在这项调查中，模拟的目的是测试不同的方法来区分社区与已知的成员和结构的统计能力。这些模拟揭示了影响测试结果解释方式的三个重要结果。首先，Integral-LIBSHUFF，TreeClimber，UniFrac，分子方差分析（AMOVA）和分子方差齐性（HOMOVA）比较了群落的结构，而不仅仅是它们的成员。其次，当一个社区结构是另一个社区结构的子集时，integral-LIBSHUFF无法检测到这种情况。第三，AMOVA确定两个或两个以上社区内的遗传多样性是否大于其合并的遗传多样性，HOMOVA确定每个社区中的遗传多样性数量是否显著不同。Integral-LIBSHUFF、TreeClimber和UniFrac在进行分析时将这些因素和其他因素混在一起，使得难以辨别社区之间检测到的差异的性质。这些发现表明，如果正确使用，当前的统计工具箱有能力解决有关微生物群落之间差异的特定生态问题。
As microbial ecology investigations have progressed from descriptive characterizations of a community to hypothesis- driven ecological research, a number of different statistical techniques have been developed to describe and compare the structure of microbial communities. Thus far, these methods have only been evaluated using 16S rRNA gene sequence data obtained from incomplete characterizations of microbial communities. In this investigation, simulations were designed to test the statistical power of different methods to differentiate between communities with known memberships and structures. These simulations revealed three important results that affect how the results of the tests are interpreted. First, integral-LIBSHUFF, TreeClimber, UniFrac, analysis of molecular variance ( AMOVA) and homogeneity of molecular variance ( HOMOVA) compare the structure of communities and not just their memberships. Second, integral-LIBSHUFF is unable to detect cases when one community structure is a subset of another. Third, AMOVA determines whether the genetic diversity within two or more communities is greater than their pooled genetic diversity, and HOMOVA determines whether the amount of genetic diversity in each community is significantly different. integral-LIBSHUFF, TreeClimber and UniFrac lump these and other factors together when performing their analysis making it difficult to discern the nature of the differences that are detected between communities. These findings demonstrate that when correctly employed, the current statistical toolbox has the ability to address specific ecological questions concerning the differences between microbial communities.