ArticlePloS one2019
Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samples.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
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- Varietal Differences in Kidney Beans Modulate Gut Microbiota and Inflammation During High-Fat Diet-Induced Obesity in Male Mice.Nutrients · 2026Article
- Microbial Community Shifts and Nitrogen Utilization in Peritidal Microbialites: The Role of Salinity and pH in Microbially Induced Carbonate Precipitation.Microbial ecology · 2025Article
- Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.Frontiers in microbiology · 2025Article
- Using Phylogeny and a Conserved Genomic Neighborhood Analysis to Extract and Visualize Gene Sets Involved in Target Gene Function: The Case of [NiFe]-hydrogenase and Succinate Dehydrogenase.Microbes and environments · 2025Article
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- Previse preterm birth in early pregnancy through vaginal microbiome signatures using metagenomics and dipstick assays.iScience · 2024Article
- Temporal dynamics of fecal microbiota community succession in broiler chickens, calves, and piglets under aerobic exposure.Microbiology spectrum · 2024Article
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- EPIK: precise and scalable evolutionary placement with informative k-mers.Bioinformatics (Oxford, England) · 2023Article
- Association of gut microbial dysbiosis with disease severity, response to therapy and disease outcomes in Indian patients with COVID-19.Gut pathogens · 2023Article
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- Network analysis of 16S rRNA sequences suggests microbial keystone taxa contribute to marine NCommunications biology · 2023Article
- Phenol and Polyaromatic Hydrocarbons Are Stronger Drivers Than Host Plant Species in Shaping the Arbuscular Mycorrhizal Fungal Component of the Mycorrhizosphere.International journal of molecular sciences · 2022Article
- Assembly of root-associated N2O-reducing communities of annual crops is governed by selection for nosZ clade I over clade II.FEMS microbiology ecology · 2022Article
- Cultivating marine bacteria under laboratory conditions: Overcoming the "unculturable" dogma.Frontiers in bioengineering and biotechnology · 2022Article
- Metagenomic Analysis Using Phylogenetic Placement-A Review of the First Decade.Frontiers in bioinformatics · 2022Review
- Ecological memory of recurrent drought modifies soil processes via changes in soil microbial community.Nature communications · 2021Article
- Microbiome Aggregated Traits and Assembly Are More Sensitive to Soil Management than Diversity.mSystems · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe exponential decrease in molecular sequencing cost generates unprecedented amounts of data. Hence, scalable methods to analyze these data are required. Phylogenetic (or Evolutionary) Placement methods identify the evolutionary provenance of anonymous sequences with respect to a given reference phylogeny. This increasingly popular method is deployed for scrutinizing metagenomic samples from environments such as water, soil, or the human gut. NOVEL
methodsHere, we present novel and, more importantly, highly scalable methods for analyzing phylogenetic placements of metagenomic samples. More specifically, we introduce methods for (a) visualizing differences between samples and their correlation with associated meta-data on the reference phylogeny, (b) clustering similar samples using a variant of the k-means method, and (c) finding phylogenetic factors using an adaptation of the Phylofactorization method. These methods enable to interpret metagenomic data in a phylogenetic context, to find patterns in the data, and to identify branches of the phylogeny that are driving these patterns.
resultsTo demonstrate the scalability and utility of our methods, as well as to provide exemplary interpretations of our methods, we applied them to 3 publicly available datasets comprising 9782 samples with a total of approximately 168 million sequences. The results indicate that new biological insights can be attained via our methods.
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