ArticleBioinformatics (Oxford, England)2020
phylogenize: correcting for phylogeny reveals genes associated with microbial distributions.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Phylogenize2: robust phylogenetic methods link genes to phenotypes across host-associated and environmental microbiomes.bioRxiv : the preprint server for biology · 2026Article
- A robust, sensitive phylogenetic method enables gene-level metagenomic analyses.bioRxiv : the preprint server for biology · 2026Article
- Integrating phylogenetic and functional data in microbiome studies.Bioinformatics (Oxford, England) · 2022Article
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Authors and funding
2 authors.
Funding
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Abstract
summaryPhylogenetic comparative methods are powerful but presently under-utilized ways to identify microbial genes underlying differences in community composition. These methods help to identify functionally important genes because they test for associations beyond those expected when related microbes occupy similar environments. We present phylogenize, a pipeline with web, QIIME 2 and R interfaces that allows researchers to perform phylogenetic regression on 16S amplicon and shotgun sequencing data and to visualize results. phylogenize applies broadly to both host-associated and environmental microbiomes. Using Human Microbiome Project and Earth Microbiome Project data, we show that phylogenize draws similar conclusions from 16S versus shotgun sequencing and reveals both known and candidate pathways associated with host colonization. AVAILABILITY AND IMPLEMENTATION: phylogenize is available at https://phylogenize.org and https://bitbucket.org/pbradz/phylogenize. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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