ArticleGenome medicine2016
An adaptive association test for microbiome data.
Article in Genome medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
41 citing papers in PubMed.
- Ensemble test for microbiome data.Microbiome · 2026Article
- I-SVVS: integrative stochastic variational variable selection to explore joint patterns of multi-omics microbiome data.Briefings in bioinformatics · 2025Article
- Multidimensional scaling improves distance-based clustering for microbiome data.Bioinformatics (Oxford, England) · 2025Article
- A unified combination framework for dependent tests with applications to microbiome association studies.Biometrics · 2025Article
- Article
- PhyImpute and UniFracImpute: two imputation approaches incorporating phylogeny information for microbial count data.Briefings in bioinformatics · 2024Article
- Phylogenetic association analysis with conditional rank correlation.Biometrika · 2024Article
- MIDASim: a fast and simple simulator for realistic microbiome data.Microbiome · 2024Article
- An adaptive direction-assisted test for microbiome compositional data.Bioinformatics (Oxford, England) · 2022Article
- Phylogeny-guided microbiome OTU-specific association test (POST).Microbiome · 2022Article
- CBEA: Competitive balances for taxonomic enrichment analysis.PLoS computational biology · 2022Article
- Adaptive and powerful microbiome multivariate association analysis via feature selection.NAR genomics and bioinformatics · 2022Article
- Associations and recovery dynamics of the nasopharyngeal microbiota during influenza-like illness in the aging population.Scientific reports · 2022Article
- Testing microbiome association using integrated quantile regression models.Bioinformatics (Oxford, England) · 2022Article
- A Simultaneous Feature Selection and Compositional Association Test for Detecting Sparse Associations in High-Dimensional Metagenomic Data.Frontiers in microbiology · 2022Article
- An Adaptive and Robust Test for Microbial Community Analysis.Frontiers in genetics · 2022Article
- CombiningFrontiers in microbiology · 2022Article
- Beta-diversity distance matrices for microbiome sample size and power calculations - How to obtain good estimates.Computational and structural biotechnology journal · 2022Article
- A Statistical Method for Association Analysis of Cell Type Compositions.Statistics in biosciences · 2021Article
- InTACT: An adaptive and powerful framework for joint-tissue transcriptome-wide association studies.Genetic epidemiology · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
There is increasing interest in investigating how the compositions of microbial communities are associated with human health and disease. Although existing methods have identified many associations, a proper choice of a phylogenetic distance is critical for the power of these methods. To assess an overall association between the composition of a microbial community and an outcome of interest, we present a novel multivariate testing method called aMiSPU, that is joint and highly adaptive over all observed taxa and thus high powered across various scenarios, alleviating the issue with the choice of a phylogenetic distance. Our simulations and real-data analyses demonstrated that the aMiSPU test was often more powerful than several competing methods while correctly controlling type I error rates. The R package MiSPU is available at https://github.com/ChongWu-Biostat/MiSPU and CRAN.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.