plot_loadings: Plot loadings of a principal component

In RNAseqQC: Quality Control for RNA-Seq Data

Plot loadings of a principal component

Description

Plot loadings of a principal component

Usage

plot_loadings(
  pca_res,
  PC = 1,
  square = FALSE,
  color_by = NULL,
  annotate_top_n = 0,
  highlight_genes = NULL,
  show_plot = TRUE
)

Arguments

pca_res	A result returned from plot_pca()
PC	Number of the principal component to plot
square	Whether to plot squared loadings. The squared loading is equal to the fraction of variance explained by the respective feature in the given principal component.
color_by	Variable (column in pca_res$loadings) to color points by. Can also be 'pc_sign' to color by the sign of the loading (useful in combination with the square = TRUE parameter).
annotate_top_n	Annotate the top n features with positive or negative loading
highlight_genes	Vector of gene names or gene IDs to highlight on the plot (overwrites top_n annotation)
show_plot	Whether to show the plot

Value

The function displays the loadings plot and returns invisible a list of the plot, the data.frame of the PCA loadings.

Examples

set.seed(1)
data <- matrix(rnorm(100*6), ncol=6)
data <- t(t(data)+c(-1, -1.1, -1.2, 1, 1.1, 1.2))
pca_res <- plot_pca(data)
plot_loadings(pca_res)

RNAseqQC documentation built on July 1, 2024, 9:07 a.m.