MVP.PCAplot: PCA Plot

In XiaoleiLiuBio/MVP: Memory-Efficient, Visualize-Enhanced, Parallel-Accelerated GWAS Tool

PCA Plot

Description

PCA Plot

Usage

MVP.PCAplot(
  PCA,
  memo = "MVP",
  col = NULL,
  pch = NULL,
  class = NULL,
  legend.pos = "topright",
  Ncluster = 1,
  plot3D = FALSE,
  file.type = "pdf",
  dpi = 300,
  box = FALSE,
  file.output = TRUE,
  outpath = getwd(),
  verbose = TRUE
)

Arguments

PCA	Principal component analysis result, 2-column matrix
memo	the prefix of the output image file.
col	colors for each cluster
pch	Either an integer specifying a symbol or a single character to be used as the default in plotting points. See points for possible values and their interpretation. Note that only integers and single-character strings can be set as a graphics parameter (and not NA nor NULL).
class	the class of all individuals, for example: "breed", "location"
legend.pos	position of legend. default is "topright"
Ncluster	cluster number
plot3D	(DEPRECATED)if TRUE, plot PC figure in 3D format, it can be only used in windows and mac operation system, "rgl" package should be installed beforehead
file.type	Character. Options are jpg, pdf, and tiff
dpi	Number. Dots per inch for .jpg and .tiff files
box	Logical value. If TRUE, the border line of Manhattan plot will be added
file.output	Logical value. If TRUE, the figures will be generated.
outpath	Effective only when file.output = TRUE, determines the path of the output file
verbose	whether to print detail.

Value

Output file: MVP.PCA_2D.<type>

Examples

genoPath <- system.file("extdata", "06_mvp-impute", "mvp.imp.geno.desc", package = "rMVP")
geno <- attach.big.matrix(genoPath)
pca <- MVP.PCA(M=geno, cpu=1)

MVP.PCAplot(PCA=pca, Ncluster=3, class=NULL, 
    col=c("red", "green", "yellow"), file.output=FALSE, pch=19)

XiaoleiLiuBio/MVP documentation built on April 11, 2024, 1:20 a.m.