SUMMARY: In fields, such as ecology, microbiology and genomics, non-Euclidean distances are widely applied to describe pairwise dissimilarity between samples. Given these pairwise distances, principal coordinates analysis is commonly used to construct a visualization of the data. However, confounding covariates can make patterns related to the scientific question of interest difficult to observe. We provide adjusted principal coordinates analysis as an easy-to-use tool, available as both an R package and a Shiny app, to improve data visualization in this context, enabling enhanced presentation of the effects of interest. AVAILABILITY AND IMPLEMENTATION: The R package 'aPCoA' and Shiny app can be accessed at https://cran.r-project.org/web/packages/aPCoA/index.html and https://biostatistics.mdanderson.org/shinyapps/aPCoA/.
SUMMARY: In fields, such as ecology, microbiology and genomics, non-Euclidean distances are widely applied to describe pairwise dissimilarity between samples. Given these pairwise distances, principal coordinates analysis is commonly used to construct a visualization of the data. However, confounding covariates can make patterns related to the scientific question of interest difficult to observe. We provide adjusted principal coordinates analysis as an easy-to-use tool, available as both an R package and a Shiny app, to improve data visualization in this context, enabling enhanced presentation of the effects of interest. AVAILABILITY AND IMPLEMENTATION: The R package 'aPCoA' and Shiny app can be accessed at https://cran.r-project.org/web/packages/aPCoA/index.html and https://biostatistics.mdanderson.org/shinyapps/aPCoA/.
Authors: Erick Riquelme; Yu Zhang; Liangliang Zhang; Maria Montiel; Michelle Zoltan; Wenli Dong; Pompeyo Quesada; Ismet Sahin; Vidhi Chandra; Anthony San Lucas; Paul Scheet; Hanwen Xu; Samir M Hanash; Lei Feng; Jared K Burks; Kim-Anh Do; Christine B Peterson; Deborah Nejman; Ching-Wei D Tzeng; Michael P Kim; Cynthia L Sears; Nadim Ajami; Joseph Petrosino; Laura D Wood; Anirban Maitra; Ravid Straussman; Matthew Katz; James Robert White; Robert Jenq; Jennifer Wargo; Florencia McAllister Journal: Cell Date: 2019-08-08 Impact factor: 41.582