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微生物组数据的贝叶斯图形成分回归AI 解读

An important task in microbiome studies is to test the existence of and give characterization to differences in the microbiome composition across groups of samples. Important challenges of this problem include the large within-group heterogeneities among samples and the existence of potential confounding variables that, when ignored, increase the chance of false discoveries and reduce the power for identifying true differences. We propose a probabilistic framework to…

用于依赖关系检验的 Fisher 精确扫描AI 解读

We introduce a method—called Fisher exact scanning (FES)—for testing and identifying variable dependency that generalizes Fisher’s exact test on 2 × 2 contingency tables to R × C contingency tables and continuous sample spaces. FES proceeds through scanning over the sample space using windows in the form of 2 × 2 tables of various sizes, and on each window completing a Fisher’s exact test. Based on a factorization of Fisher’s multivariate hypergeometric (MHG) likelihood into…