UniFrac: a New Phylogenetic Method for Comparing Microbial Communities

By Catherine A. Lozupone, Rob Knight. Applied and Environmental Microbiology, 2005

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View Paper: https://www.semanticscholar.org/paper/4da27cd0db58cf6d8525a06dd5def1584acb0de8

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Citations in the corpus

454 Pyrosequencing reveals bacterial diversity of activated sludge from 14 sewage treatment plants (2011, methodology): “Using computational ecology tools such as the UniFrac b-diversity metric (Lozupone and Knight, 2005) and principal coordinates analysis (PCoA), researchers can compare differences in microbial communities between ecosystems and along environmental gradients.”
Ecological and evolutionary forces shaping microbial diversity in the human intestine. (2006, methodology): “In experiments with C57Bl/6 mice, we showed that animals inherited their microbial communities from their mothers (Ley et al., 2005), using the recently developed UniFrac metric (Lozupone and Knight, 2005).”
Performance, Accuracy, and Web Server for Evolutionary Placement of Short Sequence Reads under Maximum Likelihood (2011, neutral): “In a typical application scenario, one may determine the diversity of the environmental sample for every replicate using, for instance , UniFrac (Lozupone and Knight 2005), and then compute an average diversity over all replicates.”
Effects of library size variance, sparsity, and compositionality on the analysis of microbiome data (2015, methodology): “Without normalization, the estimated effect size 440 of sample type for unweighted UniFrac distance was R2=0.40.”
Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate (2013, methodology): “This method was used to determine significant fitness between geographical coordinates along linear axes and sample ordination on phylogenetic (bacterial 16S rRNA weighted UniFrac) (28) or taxonomic dissimilarity (fungal ITS Bray–Curtis) unweighted pair group method with arithmetic mean (UPGMA) tree”
Human oral, gut, and plaque microbiota in patients with atherosclerosis (2010, methodology): “To compare diversity between samples, we used the weighted and unweighted UniFrac distance metrics (55, 56) using a random sample of 1,700 sequences per sample (one atherosclerotic plaque sample had fewer than 1,500 sequences and was omitted from the analysis).”
Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2020, methodology): “To support post-profiling analyses, a convenience R script for computing weighted and unweighted UniFrac distances (Lozupone and Knight, 2005) from MetaPhlAn profiles is now available in the software repository (metaphlan/utils/calculate_unifrac.”
A general suite of fungal endophytes dominate the roots of two dominant grasses in a semiarid grassland (2010, methodology): “One of the most parsimonious phylogenetic trees was used as an input file to calculate Unifrac significance and conduct Jacknife cluster analysis and specific lineage analysis in UniFrac.”
Indirect host effect on ectomycorrhizal fungi: Leaf fall and litter quality explain changes in fungal communities on the roots of co-occurring Mediterranean oaks (2010, methodology): “A phylogenetic tree was constructed using the neighbourjoining method and both the UniFrac distance metric (Lozupone and Knight, 2005), which is calculated based on differences in the tree branch length, and the P test (Martin, 2002), which estimates similarity between communities based on tree…”
Effects of straw amendment and moisture on microbial communities in Chinese fluvo-aquic soil (2014, methodology): “, taking into account relative abundance of taxa) UniFrac (Lozupone and Knight 2005) distance matrix was performed to observe the separation in eukaryotic community composition between the treatments, and analysis of similarities (ANOSIM) using OTU data was performed to quantitatively compare the di”
Shifts in bacterial community structure associated with inputs of low molecular weight carbon compounds to soil (2010, methodology): “The UniFrac algorithm estimates the phylogenetic overlap between pairs of communities and avoids some of the pitfalls associated with comparing communities at a single level of taxonomic resolution (Lozupone and Knight, 2005; Lozupone and Knight, 2008; Hamady and Knight, 2009).”
Forensic identification using skin bacterial communities (2010, methodology): “To establish these criteria and to demonstrate the potential utility of the approach for forensic identification, we carried out three interrelated studies that combine recent developments in phylogenetic community analyses (10) with high-throughput pyrosequencing methods (11).”
Biochar alters the soil microbiome and soil function: results of next‐generation amplicon sequencing across Europe (2017, methodology): “…QIIME’s compare_alpha_diversity.py script). b diversity, the similarity between the identities of taxa and their abundances by treatment, was assessed through pairwise UNIFRAC distances (Lozupone & Knight, 2005) prior to plotting using EMPeror (V azquez-Baeza et al., 2013) or bespoke R scripts.”
Microbiota-generated metabolites promote metabolic benefits via gut-brain neural circuits. (2014, neutral): “By estimating b-diversity between samples with pairwise unweighted Unifrac distance (Lozupone and Knight, 2005) and performing principal coordinates analysis, we found that”
Correlating viral phenotypes with phylogeny: accounting for phylogenetic uncertainty. (2008, background): “Lastly, Lozupone and Knight (2005) introduced the UniFrac statistic, which measures the proportion of phylogeny branch lengths that can be unambiguously associated with a particular trait value.”