heatmap_loading: Heatmap of standardized loadings

In ucsf-ferguson-lab/syndRomics: Component loading interpretation and visualization with syndromic plots

Heatmap of standardized loadings

Description

Plot a heatmap of the standardized loadings from a PCA solution.

Usage

heatmap_loading(
  pca,
  pca_data,
  ndim = 1:10,
  cutoff = 0,
  legend_title = "s. loading",
  text_values = TRUE,
  star_values = F,
  text_size = 2,
  vars = NULL,
  colors = c("steelblue1", "white", "firebrick1")
)

Arguments

pca	Object of class prcomp, princals, or data.frame. If object is a prcomp or princals object, pca_data is required, and the loadings will be extracted. If object is a data.frame object, the dataframe needs to be formatted as: first column named Variables and all other columns corresponding to a PC. One row per variable. The values are the loadings.
pca_data	Data passed to the prcomp or princals function.
ndim	Numeric. Number of PCs to plot
cutoff	Numeric or numeric vector of length ndim. Value of the loadings threshold (i.e. |loadings| >= cutoff) to plot with stars. Default = 0
legend_title	String. Title of the legend. 's. loading' by default.
text_values	Logical. Whether to plot the values of the loadings or not. Default= TRUE
star_values	Logical. Whether to plot a star in |loadings|>=cutoff. Only relevant if text_values=FALSE. Default=FALSE
text_size	Numeric. Size of the text_values.
vars	Character vector. Variables will be ordered as the provided variable names. Non-specified variables will be excluded from the plot. By default variables are ordered in alphabetically by ggplot.
colors	Character vector of length 3. Vector with the character name or hexadecimal number (e.g. "#FF0000") of three colors, the lower color, the middle color and the higher color for the gradient used in the plot. Hexadecimal number can be obtained using rgb for example.

Value

Returns a ggplot2 object.

Author(s)

Abel Torres Espin

Examples

data(mtcars)
pca_mtcars<-prcomp(mtcars, center = TRUE, scale. = TRUE)

heatmap_loading(pca = pca_mtcars, pca_data = mtcars, ndim = 1:4)

ucsf-ferguson-lab/syndRomics documentation built on June 26, 2022, 5:36 p.m.