The Phylogenetic Structure of β -diversity: Covariance Matrix Sparsification of Critical Beta-splitting Trees

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The paper studies whether Haar-like wavelets can sparsify phylogenetic covariance matrices and support a β-diversity metric (“Haar-like distance”) that ranks splits of a reference phylogeny by their contribution to compositional differences between two microbial environments. Using an ensemble of large critical beta-splitting random trees to better reflect “real-world” phylogenies than uniformly random k-regular trees, the authors compute sharp asymptotic estimates for the first and second moments of external path length and show that the Haar-like basis still approximately pseudo-diagonalizes the phylogenetic covariance matrix for most large trees. They also develop a statistical test to evaluate the significance of splits highlighted by the Haar-like distance and apply it to a microbial mat dataset to support the claim that identified splits correspond to biological signals. The paper explicitly notes a limitation that earlier results from uniform binary trees may have different statistical features, making applicability uncertain and motivating the critical beta-splitting model. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Haar-like wavelets sparsify the phylogenetic covariance matrices of large, uniformly random k -regular trees with overwhelmingly high probability. This motivates the Haar-like distance, a β -diversity metric that implicitly ranks the splits of a reference phylogeny by their relevance in differentiating two microbial environments, offering an interpretation as to why the environments differ compositionally. Nevertheless, uniform binary trees exhibit statistical features distinct from those of the trees used by practitioners, leaving the extent of sparsification and the practical validity of the implied Haar-like distance speculative. To address this, our manuscript examines the sparsification of phylogenetic covariance matrices of large critical beta-splitting random trees, a model introduced to better reflect real-world phylogenies. By obtaining sharp asymptotic estimates of the first and second moments of the external path length in this ensemble, we demonstrate that the Haar-like basis also pseudo-diagonalizes the phylogenetic covariance matrix of most large trees in this more realistic framework. Additionally, we devise a test to assess the statistical significance of splits in the reference phylogeny identified by the Haar-like distance. We apply the test to a well-studied microbial mat to further substantiate the presumption that the identified splits represent genuine biological signals differentiating the top and bottom layers of the mat.
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Abstract Haar-like wavelets sparsify the phylogenetic covariance matrices of large, uniformly random k-regular trees with overwhelmingly high probability. This motivates the Haar-like distance, a β-diversity metric that implicitly ranks the splits of a reference phylogeny by their relevance in differentiating two microbial environments, offering an interpretation as to why the environments differ compositionally. Nevertheless, uniform binary trees exhibit statistical features distinct from those of the trees used by practitioners, leaving the extent of sparsification and the practical validity of the implied Haar-like distance speculative. To address this, our manuscript examines the sparsification of phylogenetic covariance matrices of large critical beta-splitting random trees, a model introduced to better reflect real-world phylogenies. By obtaining sharp asymptotic estimates of the first and second moments of the external path length in this ensemble, we demonstrate that the Haar-like basis also pseudo-diagonalizes the phylogenetic covariance matrix of most large trees in this more realistic framework. Additionally, we devise a test to assess the statistical significance of splits in the reference phylogeny identified by the Haar-like distance. We apply the test to a well-studied microbial mat to further substantiate the presumption that the identified splits represent genuine biological signals differentiating the top and bottom layers of the mat. Competing Interest Statement The authors have declared no competing interest.

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License: CC-BY-4.0