Literature DB >> 22174277

Comparisons of distance methods for combining covariates and abundances in microbiome studies.

Julia Fukuyama1, Paul J McMurdie, Les Dethlefsen, David A Relman, Susan Holmes.   

Abstract

This article compares different methods for combining abundance data, phylogenetic trees and clinical covariates in a nonparametric setting. In particular we study the output from the principal coordinates analysis on UNIFRAC and WEIGHTED UNIFRAC distances and the output from a double principal coordinate analyses DPCOA using distances computed on the phylogenetic tree. We also present power comparisons for some of the standard tests of phylogenetic signal between different types of samples. These methods are compared both on simulated and real data sets. Our study shows that DPCoA is less robust to outliers, and more robust to small noisy fluctuations around zero.

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Year:  2012        PMID: 22174277      PMCID: PMC4532668     

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  12 in total

1.  From dissimilarities among species to dissimilarities among communities: a double principal coordinate analysis.

Authors:  Sandrine Pavoine; A-B Anne-Béatrice Dufour; Daniel Chessel
Journal:  J Theor Biol       Date:  2004-06-21       Impact factor: 2.691

2.  Picante: R tools for integrating phylogenies and ecology.

Authors:  Steven W Kembel; Peter D Cowan; Matthew R Helmus; William K Cornwell; Helene Morlon; David D Ackerly; Simon P Blomberg; Campbell O Webb
Journal:  Bioinformatics       Date:  2010-04-15       Impact factor: 6.937

3.  Diversity of the human intestinal microbial flora.

Authors:  Paul B Eckburg; Elisabeth M Bik; Charles N Bernstein; Elizabeth Purdom; Les Dethlefsen; Michael Sargent; Steven R Gill; Karen E Nelson; David A Relman
Journal:  Science       Date:  2005-04-14       Impact factor: 47.728

4.  Testing for phylogenetic signal in phenotypic traits: new matrices of phylogenetic proximities.

Authors:  Sandrine Pavoine; Sébastien Ollier; Dominique Pontier; Daniel Chessel
Journal:  Theor Popul Biol       Date:  2007-10-12       Impact factor: 1.570

5.  Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

Authors:  Patrick D Schloss; Sarah L Westcott; Thomas Ryabin; Justine R Hall; Martin Hartmann; Emily B Hollister; Ryan A Lesniewski; Brian B Oakley; Donovan H Parks; Courtney J Robinson; Jason W Sahl; Blaz Stres; Gerhard G Thallinger; David J Van Horn; Carolyn F Weber
Journal:  Appl Environ Microbiol       Date:  2009-10-02       Impact factor: 4.792

6.  The detection of disease clustering and a generalized regression approach.

Authors:  N Mantel
Journal:  Cancer Res       Date:  1967-02       Impact factor: 12.701

7.  Phyloseq: a bioconductor package for handling and analysis of high-throughput phylogenetic sequence data.

Authors:  Paul J McMurdie; Susan Holmes
Journal:  Pac Symp Biocomput       Date:  2012

8.  QIIME allows analysis of high-throughput community sequencing data.

Authors:  J Gregory Caporaso; Justin Kuczynski; Jesse Stombaugh; Kyle Bittinger; Frederic D Bushman; Elizabeth K Costello; Noah Fierer; Antonio Gonzalez Peña; Julia K Goodrich; Jeffrey I Gordon; Gavin A Huttley; Scott T Kelley; Dan Knights; Jeremy E Koenig; Ruth E Ley; Catherine A Lozupone; Daniel McDonald; Brian D Muegge; Meg Pirrung; Jens Reeder; Joel R Sevinsky; Peter J Turnbaugh; William A Walters; Jeremy Widmann; Tanya Yatsunenko; Jesse Zaneveld; Rob Knight
Journal:  Nat Methods       Date:  2010-04-11       Impact factor: 28.547

9.  UniFrac: a new phylogenetic method for comparing microbial communities.

Authors:  Catherine Lozupone; Rob Knight
Journal:  Appl Environ Microbiol       Date:  2005-12       Impact factor: 4.792

10.  Evolution of mammals and their gut microbes.

Authors:  Ruth E Ley; Micah Hamady; Catherine Lozupone; Peter J Turnbaugh; Rob Roy Ramey; J Stephen Bircher; Michael L Schlegel; Tammy A Tucker; Mark D Schrenzel; Rob Knight; Jeffrey I Gordon
Journal:  Science       Date:  2008-05-22       Impact factor: 47.728

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  21 in total

1.  A significance test for graph-constrained estimation.

Authors:  Sen Zhao; Ali Shojaie
Journal:  Biometrics       Date:  2015-09-22       Impact factor: 2.571

2.  Selective Probiotic Treatment Positively Modulates the Microbiota-Gut-Brain Axis in the BTBR Mouse Model of Autism.

Authors:  Angela Pochakom; Chunlong Mu; Jong M Rho; Thomas A Tompkins; Shyamchand Mayengbam; Jane Shearer
Journal:  Brain Sci       Date:  2022-06-14

Review 3.  Characterization of the gut microbiome in epidemiologic studies: the multiethnic cohort experience.

Authors:  Benjamin C Fu; Timothy W Randolph; Unhee Lim; Kristine R Monroe; Iona Cheng; Lynne R Wilkens; Loïc Le Marchand; Meredith A J Hullar; Johanna W Lampe
Journal:  Ann Epidemiol       Date:  2016-03-08       Impact factor: 3.797

4.  KERNEL-PENALIZED REGRESSION FOR ANALYSIS OF MICROBIOME DATA.

Authors:  Timothy W Randolph; Sen Zhao; Wade Copeland; Meredith Hullar; Ali Shojaie
Journal:  Ann Appl Stat       Date:  2018-03-09       Impact factor: 2.083

5.  Associating microbiome composition with environmental covariates using generalized UniFrac distances.

Authors:  Jun Chen; Kyle Bittinger; Emily S Charlson; Christian Hoffmann; James Lewis; Gary D Wu; Ronald G Collman; Frederic D Bushman; Hongzhe Li
Journal:  Bioinformatics       Date:  2012-06-17       Impact factor: 6.937

6.  Coral-Associated Bacterial Diversity Is Conserved across Two Deep-Sea Anthothela Species.

Authors:  Stephanie N Lawler; Christina A Kellogg; Scott C France; Rachel W Clostio; Sandra D Brooke; Steve W Ross
Journal:  Front Microbiol       Date:  2016-04-05       Impact factor: 5.640

7.  Piglet nasal microbiota at weaning may influence the development of Glässer's disease during the rearing period.

Authors:  Florencia Correa-Fiz; Lorenzo Fraile; Virginia Aragon
Journal:  BMC Genomics       Date:  2016-05-26       Impact factor: 3.969

8.  Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies.

Authors:  Jonathan Thorsen; Asker Brejnrod; Martin Mortensen; Morten A Rasmussen; Jakob Stokholm; Waleed Abu Al-Soud; Søren Sørensen; Hans Bisgaard; Johannes Waage
Journal:  Microbiome       Date:  2016-11-25       Impact factor: 14.650

9.  An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data.

Authors:  W Duncan Wadsworth; Raffaele Argiento; Michele Guindani; Jessica Galloway-Pena; Samuel A Shelburne; Marina Vannucci
Journal:  BMC Bioinformatics       Date:  2017-02-08       Impact factor: 3.169

10.  High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions.

Authors:  Amnon Amir; Amit Zeisel; Or Zuk; Michael Elgart; Shay Stern; Ohad Shamir; Peter J Turnbaugh; Yoav Soen; Noam Shental
Journal:  Nucleic Acids Res       Date:  2013-11-07       Impact factor: 16.971

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