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Generalized UniFrac

eagle-i ID

http://eagle-i.itmat.upenn.edu/i/0000013a-c2c1-63a1-d69a-d90d80000000

Resource Type

  1. Algorithmic software component

Properties

  1. Resource Description
    The human microbiome plays an important role in human disease and health. Identification of factors that affect the microbiome composition can provide insights into disease mechanism as well as suggest ways to modulate the microbiome composition for therapeutical purposes. Distance-based statistical tests have been applied to test the association of microbiome composition with environmental or biological covariates. The unweighted and weighted UniFrac distances are the most widely used distance measures. However, these two measures assign too much weight either to rare lineages or to most abundant lineages, which can lead to loss of power when the important composition change occurs in moderately abundant lineages. We develop generalized UniFrac distances that extend the weighted and unweighted UniFrac distances for detecting a much wider range of biologically relevant changes.
  2. Additional Name
    GUniFrac
  3. Used by
    Statistical Genetics and Genomics Laboratory
  4. Version
    1.0
  5. Data Input
    Rooted phylogenetic tree of R class "phylo"
  6. Data Input
    Operational taxonomic unit count table
  7. Data Output
    Generalized UniFrac distances
  8. Related Publication or Documentation
    Associating microbiome composition with environmental covariates using generalized UniFrac distances
  9. Website(s)
    http://cran.r-project.org/web/packages/GUniFrac/index.html
  10. Related Technique
    Metagenomics analysis
  11. Developed by
    Li, Hongzhe., PhD
  12. Software license
    GNU General Public License
  13. Coded in
    R language
 
RDFRDF
 
Provenance Metadata About This Resource Record
  1. workflow state
    Published
  2. contributor
    ggrant (Gregory Grant)
  3. created
    2012-11-02T16:18:44.514-04:00
  4. creator
    fcoldren
  5. modified
    2020-02-11T14:10:29.890-05:00
Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016