biplot: biplot methods for 'pca' family

In mixOmicsTeam/mixOmics: Omics Data Integration Project

biplot methods for pca family

Description

biplot methods for pca family

Usage

## S3 method for class 'pca'
biplot(
  x,
  comp = c(1, 2),
  block = NULL,
  ind.names = TRUE,
  group = NULL,
  cutoff = 0,
  col.per.group = NULL,
  col = NULL,
  ind.names.size = 3,
  ind.names.col = color.mixo(4),
  ind.names.repel = TRUE,
  pch = 19,
  pch.levels = NULL,
  pch.size = 2,
  var.names = TRUE,
  var.names.col = "grey40",
  var.names.size = 4,
  var.names.angle = FALSE,
  var.arrow.col = "grey40",
  var.arrow.size = 0.5,
  var.arrow.length = 0.2,
  ind.legend.title = NULL,
  vline = FALSE,
  hline = FALSE,
  legend = if (is.null(group)) FALSE else TRUE,
  legend.title = NULL,
  pch.legend.title = NULL,
  cex = 1.05,
  ...
)

## S3 method for class 'mixo_pls'
biplot(
  x,
  comp = c(1, 2),
  block = NULL,
  ind.names = TRUE,
  group = NULL,
  cutoff = 0,
  col.per.group = NULL,
  col = NULL,
  ind.names.size = 3,
  ind.names.col = color.mixo(4),
  ind.names.repel = TRUE,
  pch = 19,
  pch.levels = NULL,
  pch.size = 2,
  var.names = TRUE,
  var.names.col = "grey40",
  var.names.size = 4,
  var.names.angle = FALSE,
  var.arrow.col = "grey40",
  var.arrow.size = 0.5,
  var.arrow.length = 0.2,
  ind.legend.title = NULL,
  vline = FALSE,
  hline = FALSE,
  legend = if (is.null(group)) FALSE else TRUE,
  legend.title = NULL,
  pch.legend.title = NULL,
  cex = 1.05,
  ...
)

Arguments

x	An object of class 'pca'or mixOmics '(s)pls'.
comp	integer vector of length two (or three to 3d). The components that will be used on the horizontal and the vertical axis respectively to project the individuals.
block	Character, name of the block to show for pls object. Default to 'X'.
ind.names	either a character vector of names for the individuals to be plotted, or FALSE for no names. If TRUE, the row names of the first (or second) data matrix is used as names (see Details).
group	Factor indicating the group membership for each sample.
cutoff	numeric between 0 and 1. Variables with correlations below this cutoff in absolute value are not plotted (see Details).
col.per.group	character (or symbol) color to be used when 'group' is defined. Vector of the same length as the number of groups.
col	character (or symbol) color to be used, possibly vector.
ind.names.size	Numeric, sample name size.
ind.names.col	Character, sample name colour.
ind.names.repel	Logical, whether to repel away label names.
pch	plot character. A character string or a vector of single characters or integers. See points for all alternatives.
pch.levels	If pch is a factor, a named vector providing the point characters to use. See examples.
pch.size	Numeric, sample point character size.
var.names	Logical indicating whether to show variable names. Alternatively, a character.
var.names.col	Character, variable name colour.
var.names.size	Numeric, variable name size.
var.names.angle	Logical, whether to align variable names to arrow directions.
var.arrow.col	Character, variable arrow colour. If 'NULL', no arrows are shown.
var.arrow.size	Numeric, variable arrow head size.
var.arrow.length	Numeric, length of the arrow head in 'cm'.
ind.legend.title	Character, title of the legend.
vline	Logical, whether to draw the vertical neutral line.
hline	Logical, whether to draw the horizontal neutral line.
legend	Logical, whether to show the legend if group != NULL.
legend.title	Character, the legend title if group != NULL.
pch.legend.title	Character, the legend title if pch is a factor.
cex	Numeric scalar indicating the desired magnification of plot texts. theme function may be used with the output object if further customisation is required.
...	Not currently used.
pch.legend	Character, the legend title if pch is a factor.

Details

biplot unifies the reduced representation of both the observations/samples and variables of a matrix of multivariate data on the same plot. Essentially, in the reduced space the samples are shown as points/names and the contributions of features to each dimension are shown as directed arrows or vectors. For pls objects it is possible to use either 'X' or 'Y' latent space using block argument.

Value

A ggplot object.

Author(s)

Al J Abadi

Examples

data("nutrimouse")
## --------- pca ---------- ##
pca.lipid <- pca(nutrimouse$lipid, ncomp = 3, scale = TRUE)
# seed for reproducible geom_text_repel
set.seed(42)
biplot(pca.lipid)
## correlation cutoff to filter features
biplot(pca.lipid, cutoff = c(0.8))
## tailor threshold for each component
biplot(pca.lipid, cutoff = c(0.8, 0.7))
## customise components
biplot(pca.lipid, cutoff = c(0.8), comp = c(1,3))

## customise ggplot in an arbitrary way
biplot(pca.lipid) + theme_linedraw() + 
    # add vline
    geom_vline(xintercept = 0, col = 'green') +
    # add hline
    geom_hline(yintercept = 0, col = 'green') +
    # customise labs
    labs(x = 'Principal Component 1', y = 'Principal Component 2')

## group samples
biplot(pca.lipid, group = nutrimouse$diet, legend.title = 'Diet')

## customise variable labels
biplot(pca.lipid, 
       var.names.col = color.mixo(2),
       var.names.size = 4,
       var.names.angle = TRUE
)

## no arrows
biplot(pca.lipid, group = nutrimouse$diet, legend.title = 'Diet', 
       var.arrow.col = NULL, var.names.col = 'black')

## add x=0 and y=0 lines in function
biplot(pca.lipid, group = nutrimouse$diet, legend.title = 'Diet', 
       var.arrow.col = NULL, var.names.col = 'black', 
       vline = TRUE, hline = TRUE)

## --------- spca
## example with spca
spca.lipid <- spca(nutrimouse$lipid, ncomp = 2, scale = TRUE, keepX = c(8, 6))
biplot(spca.lipid, var.names.col = 'black', group = nutrimouse$diet, 
       legend.title = 'Diet')

## --------- pls ---------- ##
data("nutrimouse")
pls.nutrimouse <- pls(X = nutrimouse$gene, Y = nutrimouse$lipid, ncomp = 2)
biplot(pls.nutrimouse, group = nutrimouse$genotype, block = 'X',
       legend.title = 'Genotype', cutoff = 0.878) 

biplot(pls.nutrimouse, group = nutrimouse$genotype, block = 'Y',
       legend.title = 'Genotype', cutoff = 0.8) 

## --------- plsda ---------- ##
data(breast.tumors)
X <- breast.tumors$gene.exp
colnames(X) <- paste0('GENE_', colnames(X))
rownames(X) <- paste0('SAMPLE_', rownames(X))
Y <- breast.tumors$sample$treatment

plsda.breast <- plsda(X, Y, ncomp = 2)
biplot(plsda.breast, cutoff = 0.72)
## remove arrows
biplot(plsda.breast, cutoff = 0.72, var.arrow.col = NULL, var.names.size = 4)

mixOmicsTeam/mixOmics documentation built on Dec. 3, 2024, 11:15 p.m.