Am J Epidemiol. 2021 Feb 1;190(3):439-447. doi: 10.1093/aje/kwaa204.
A simple method to analyze microbiome beta-diversity computes mean beta-diversity distances from a test sample to standard reference samples. We used reference stool and nasal samples from the Human Microbiome Project and regressed an outcome on mean distances (2 degrees-of-freedom (df) test) or additionally on squares and cross-product of mean distances (5-df test). We compared the power of 2-df and 5-df tests with the microbiome regression-based kernel association test (MiRKAT). In simulations, MiRKAT had moderately greater power than the 2-df test for discriminating skin versus saliva and skin versus nasal samples, but differences were negligible for skin versus stool and stool versus nasal samples. The 2-df test had slightly greater power than MiRKAT for Dirichlet multinomial samples. In associating body mass index with beta-diversity in stool samples from the American Gut Project, the 5-df test yielded smaller P values than MiRKAT for most taxonomic levels and beta-diversity measures. Unlike procedures like MiRKAT that are based on the beta-diversity matrix, mean distances to reference samples can be analyzed with standard statistical tools and shared or meta-analyzed without sharing primary DNA data. Our data indicate that standard reference tests have power comparable to MiRKAT's (and to permutational multivariate analysis of variance), but more simulations and applications are needed to confirm this.
一种分析微生物组β多样性的简单方法是计算测试样本与标准参考样本之间的平均β多样性距离。我们使用人类微生物组计划的参考粪便和鼻腔样本,并根据平均距离进行回归分析(2 个自由度(df)检验),或者根据平均距离的平方和交叉乘积进行回归分析(5-df 检验)。我们将 2-df 和 5-df 检验的功效与基于微生物组回归的核关联检验(MiRKAT)进行了比较。在模拟中,MiRKAT 在区分皮肤与唾液以及皮肤与鼻腔样本方面比 2-df 检验具有更高的辨别力,但在皮肤与粪便以及粪便与鼻腔样本方面差异可以忽略不计。对于 Dirichlet 多项分布样本,2-df 检验比 MiRKAT 具有略高的辨别力。在将体重指数与美国肠道计划中粪便样本的β多样性相关联时,5-df 检验在大多数分类水平和β多样性度量方面产生的 P 值小于 MiRKAT。与 MiRKAT 等基于β多样性矩阵的方法不同,到参考样本的平均距离可以使用标准统计工具进行分析,无需共享原始 DNA 数据即可共享或进行荟萃分析。我们的数据表明,标准参考测试的功效与 MiRKAT(以及置换多元方差分析)相当,但需要更多的模拟和应用来证实这一点。