MiRKAT：基于核机器回归的微生物组全局关联检验。
MiRKAT: kernel machine regression-based global association tests for the microbiome.
机构信息
Department of Mathematics and Statistics, Williams College, Williamstown, MA 01267, USA.
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
出版信息
Bioinformatics. 2021 Jul 12;37(11):1595-1597. doi: 10.1093/bioinformatics/btaa951.
Abstract
SUMMARY
Distance-based tests of microbiome beta diversity are an integral part of many microbiome analyses. MiRKAT enables distance-based association testing with a wide variety of outcome types, including continuous, binary, censored time-to-event, multivariate, correlated and high-dimensional outcomes. Omnibus tests allow simultaneous consideration of multiple distance and dissimilarity measures, providing higher power across a range of simulation scenarios. Two measures of effect size, a modified R-squared coefficient and a kernel RV coefficient, are incorporated to allow comparison of effect sizes across multiple kernels.
AVAILABILITY AND IMPLEMENTATION
MiRKAT is available on CRAN as an R package.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
摘要
摘要
基于距离的微生物组β多样性检验是许多微生物组分析的一个组成部分。MiRKAT 支持与各种结果类型（包括连续型、二分类型、删失时间事件型、多变量型、相关型和高维型）的基于距离的关联检验。整体检验允许同时考虑多种距离和不相似性度量，在一系列模拟场景中提供更高的功效。两个效应大小度量，一个修正的 R 平方系数和一个核随机变量系数，被合并以允许在多个核之间比较效应大小。
可用性和实现
MiRKAT 作为一个 R 包在 CRAN 上可用。
补充信息
补充数据可在“Bioinformatics”在线获取。
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