visualizeFullFamily: Shiny gadget for adaptive gPCA

In adaptiveGPCA: Adaptive Generalized PCA

Shiny gadget for adaptive gPCA

Description

Shiny gadget that shows the ordinations from an entire family of gPCAs and returns a gPCA object with the one selected by the user.

Usage

visualizeFullFamily(fullFamily, sample_data = NULL,
  sample_mapping = aes_string(x = "Axis1", y = "Axis2"),
  sample_facet = NULL, var_data = NULL, var_mapping = aes_string(x =
  "Axis1", y = "Axis2"), layout = c(2, 6))

Arguments

fullFamily	The output from gpcaFullFamily
sample_data	Optional data used for plotting the samples
sample_mapping	An aesthetic mapping to be passed to ggplot for plotting the samples
sample_facet	A ggplot faceting command used for faceting the samples.
var_data	Optional data used for plotting the variables
var_mapping	An aesthetic mapping to be passed to ggplot for plotting the variables
layout	A vector of length 2. The first number gives the number of columns (out of 12) for the sidebar, the second number gives the number of columns (out of 12) for the sample plot in the main panel.

Value

This function will open a 'shiny' app in a browser window. You can investigate the results for different values of r with this app. Once you press the 'done' button, the app will close and the function will return an R object containing the results for the value of r (the regularization parameter) that was chosen in the app. The returned object is a list containing the variable loadings on the principal axes (QV), the sample/row scores (U), and the fraction of the variance explained by each of the axes (vars).

Examples

## Not run: 
data(AntibioticPhyloseq)
pp = processPhyloseq(AntibioticPhyloseq)
out.ff = gpcaFullFamily(pp$X, Q = pp$Q, D = pp$D, k = 2)
out.agpca = visualizeFullFamily(out.ff,
    sample_data = sample_data(AntibioticPhyloseq),
    sample_mapping = aes(x = Axis1, y = Axis2, color = condition),
    var_data = tax_table(AntibioticPhyloseq),
    var_mapping = aes(x = Axis1, y = Axis2, color = Phylum))

## End(Not run)

adaptiveGPCA documentation built on Dec. 8, 2022, 5:12 p.m.