2011
DOI: 10.1186/1471-2105-12-118
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Variance adjusted weighted UniFrac: a powerful beta diversity measure for comparing communities based on phylogeny

Abstract: BackgroundBeta diversity, which involves the assessment of differences between communities, is an important problem in ecological studies. Many statistical methods have been developed to quantify beta diversity, and among them, UniFrac and weighted-UniFrac (W-UniFrac) are widely used. The W-UniFrac is a weighted sum of branch lengths in a phylogenetic tree of the sequences from the communities. However, W-UniFrac does not consider the variation of the weights under random sampling resulting in less power detec… Show more

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Cited by 129 publications
(98 citation statements)
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“…A recently proposed variance adjusted UniFrac distance ( d VAW ) (Chang et al ., 2011) is also compared in this setting. d VAW was developed to moderate the branch proportion difference by its variance and was shown to increase the power of detecting the difference between two microbial communities.…”
Section: Resultsmentioning
confidence: 99%
“…A recently proposed variance adjusted UniFrac distance ( d VAW ) (Chang et al ., 2011) is also compared in this setting. d VAW was developed to moderate the branch proportion difference by its variance and was shown to increase the power of detecting the difference between two microbial communities.…”
Section: Resultsmentioning
confidence: 99%
“…By comparing the compositions of oral communities from different time periods, we can learn how specific factors affect community development and how species or individuals associate with each other. 28 Cluster analysis using weighted UniFrac metrics (Figure 4) found that samples before radiotherapy (PT) and the early stages of radiotherapy (10 Gy, 20 Gy and 30 Gy) formed a cluster distinct from the time points at later stages of radiotherapy (40 Gy, 50 Gy and 60 Gy), indicating that there existed temporal variations in microbial communities through the course of treatment. Comparing the cluster analysis with the phylogenetic tree generated by the R program showed similar results for the distances based on genus composition (Figure 2).…”
Section: Resultsmentioning
confidence: 99%
“…Beta diversity metrics weighted by phylogenetic distance were used to generate distance matrices for further analysis (Lozupone and Knight ; Chang et al . ). NMDS plots were created in R using ggplot2 and vegan (Oksanen et al .…”
Section: Methodsmentioning
confidence: 97%