View source: R/FourHquaternaryC.R
FourHquaternaryC | R Documentation |
Draws the centroid of bootstrapped values of the 4H-index on a quaternary (four dimensional barycentric, Aitchison Simplex) plot.
FourHquaternaryC(boots,col='red',addplot=FALSE,plotgrid=TRUE,
size_centroid=15,size_font=2)
boots |
Output from the |
col |
The color of the points in the quaternary plot. The default is 'red' |
addplot |
Whether or not to add the data to an existing plot. The default is FALSE |
plotgrid |
Whether or not to plot gridlines on the quaternary plot. The default is TRUE |
size_centroid |
The size of the point representing the centroid of the bootstrap samples. The default is 15. |
size_font |
The size of the font used to label the four verticies. The default is 2. |
FourHquaternaryC
allows for visualization of the centroid of bootstrapped 4H-indices within the framework of a 4-dimensional Aitchison Simplex, also known as a 4-dimensional barycentric plot or quaternary plot. Commonly used for compositional data, the Aitchison Simplex is convenient for the 4H-index, because \mathcal{U} + \mathcal{I} + \mathcal{G} + \mathcal{L} = 1
, reflecting the fact that each of the four different conceptual models - Union, Intersection, Gain and Loss - comprise one part of the whole, where the whole is the total microbial diversity across the entire hybrid host complex. FourHquaternaryC
uses functions from the compositions
R package to transform the four coordinates of the 4H-index, such that they can be drawn on a quaternary plot.
This function plots the centroid of bootstrapped 4H-indices on quaternary plot (Aitchison Simplex, 4-dimensional barycentric plot).
Henry, L., Wickham H., et al. "rlang: Functions for Base Types and Core R and 'Tidyverse' Features" https://CRAN.R-project.org/package=rlang
Van den Boogaart, K. Gerald, and Raimon Tolosana-Delgado. "“Compositions”: a unified R package to analyze compositional data." Computers & Geosciences 34.4 (2008): 320-338.
van den Boogaart, K. Gerald, et al. "Package ‘compositions’." Compositional data analysis Ver (2013): 1-40.
van den Boogaart, K. Gerald, Tolosana-Delgado, R., Bren, M. "compositions: Compositional Data Analysis" https://CRAN.R-project.org/package=compositions
Adler, Daniel, Oleg Nenadic, and Walter Zucchini. "Rgl: A r-library for 3d visualization with opengl." Proceedings of the 35th symposium of the interface: computing science and statistics, Salt Lake City. Vol. 35. 2003.
Adler, D., Murdoch, M. D., Suggests, M. A. S. S., WebGL, P. L. Y., OBJ, S., & OpenGL, S. (2019). Package ‘rgl’.
Murdoch, Duncan, Daniel Adler, and Oleg Nenadic. "Package ‘rgl’." R Package (2023).
#Test with enterotype dataset
library(phyloseq)
data(enterotype)
#Covert the OTU table to reads, rather than fractional abundances
otu_table(enterotype)<-round(10000*otu_table(enterotype))
#Randomly assign host classes (these should be known in a real hybrid microbiome dataset)
#The two parent species are assigned '1' and '3' respectively, the hybrid is assigned '2'
hybrid_status<-sample(1:3,280, replace=TRUE)
#Bootstrap the dataset
boot_samples<-FourHbootstrap(enterotype,hybrid_status,0.5,5,10)
#Plot the centroid of the bootstrapped samples as a new quaternary plot
FourHquaternaryC(boot_samples,col='red')
#Plot the centroid of the bootstrapped samples on an existing quaternary plot
#An existing quaternary plot should already be open
FourHquaternaryC(boot_samples,col='red',addplot=TRUE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.