ArticleFrontiers in genetics2019
An Adaptive Multivariate Two-Sample Test With Application to Microbiome Differential Abundance Analysis.
Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Ensemble test for microbiome data.Microbiome · 2026Article
- Initiation of metformin in early pregnancy results in fetal bioaccumulation, growth restriction, and renal dysmorphology in a primate model.American journal of obstetrics and gynecology · 2024Article
- An adaptive direction-assisted test for microbiome compositional data.Bioinformatics (Oxford, England) · 2022Article
- LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data.BMC bioinformatics · 2022Article
- Adaptive and powerful microbiome multivariate association analysis via feature selection.NAR genomics and bioinformatics · 2022Article
- Beware to ignore the rare: how imputing zero-values can improve the quality of 16S rRNA gene studies results.BMC bioinformatics · 2022Article
- A maximum-type microbial differential abundance test with application to high-dimensional microbiome data analyses.Frontiers in cellular and infection microbiology · 2022Article
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Abstract
Differential abundance analysis is a crucial task in many microbiome studies, where the central goal is to identify microbiome taxa associated with certain biological or clinical conditions. There are two different modes of microbiome differential abundance analysis: the individual-based univariate differential abundance analysis and the group-based multivariate differential abundance analysis. The univariate analysis identifies differentially abundant microbiome taxa subject to multiple correction under certain statistical error measurements such as false discovery rate, which is typically complicated by the high-dimensionality of taxa and complex correlation structure among taxa. The multivariate analysis evaluates the overall shift in the abundance of microbiome composition between two conditions, which provides useful preliminary differential information for the necessity of follow-up validation studies. In this paper, we present a novel
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