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用于提取微生物组成的零膨胀逻辑正态多项模型AI 解读

High throughput sequencing data collected to study the microbiome provide information in the form of relative abundances and should be treated as compositions. Although many approaches including scaling and rarefaction have been proposed for converting raw count data into microbial compositions, most of these methods simply return zero values for zero counts. However, zeros can distort downstream analyses, and they can also pose problems for composition-aware methods. This…

因子增强逆回归及其微生物组数据分析应用AI 解读

We investigate the relationship between count data that inform the relative abundance of features of a composition, and factors that influence the composition. Our work is motivated from microbiome studies aiming to extract microbial signatures that are predictive of host phenotypes based on data collected from a group of individuals harboring radically different microbial communities. We introduce multinomial Factor Augmented Inverse Regression (FAIR) of the count vector…