ArticleFrontiers in microbiology2020
Incorporating Phylogenetic Information in Microbiome Differential Abundance Studies Has No Effect on Detection Power and FDR Control.
Article in Frontiers in microbiology, 2020. 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.
- Adaptive graph learning of microbial phylogeny enables accurate and interpretable microbiome-based host phenotype prediction.Applied and environmental microbiology · 2026Article
- A strategy for differential abundance analysis of sparse microbiome data with group-wise structured zeros.Scientific reports · 2024Article
- Multiscale adaptive differential abundance analysis in microbial compositional data.Bioinformatics (Oxford, England) · 2023Article
- Phylogeny-guided microbiome OTU-specific association test (POST).Microbiome · 2022Article
- Tree-aggregated predictive modeling of microbiome data.Scientific reports · 2021Article
- treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses.Genome biology · 2021Article
- tascCODA: Bayesian Tree-Aggregated Analysis of Compositional Amplicon and Single-Cell Data.Frontiers in genetics · 2021Article
- A Bayesian Negative Binomial Hierarchical Model for Identifying Diet-Gut Microbiome Associations.Frontiers in microbiology · 2021Article
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Authors and funding
4 authors.
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Abstract
We consider the problem of incorporating evolutionary information (e.g., taxonomic or phylogenic trees) in the context of metagenomics differential analysis. Recent results published in the literature propose different ways to leverage the tree structure to increase the detection rate of differentially abundant taxa. Here, we propose instead to use a different hierarchical structure, in the form of a correlation-based tree, as it may capture the structure of the data better than the phylogeny. We first show that the correlation tree and the phylogeny are significantly different before turning to the impact of tree choice on detection rates. Using synthetic data, we show that the tree does have an impact: smoothing
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