PlotMetabolitePCA: PlotMetabolitePCA.

In MetabolomicsBasics: Basic Functions to Investigate Metabolomics Data Matrices

PlotMetabolitePCA.

Description

PlotMetabolitePCA will show PC1 and PC2 of a pcaMethods object and generate a flexible plot.

Usage

PlotMetabolitePCA(
  pca_res = NULL,
  sam = NULL,
  g = NULL,
  medsd = FALSE,
  text.col = "ID",
  legend.x = "bottomleft",
  comm = NULL
)

Arguments

pca_res	A pcaRes object from the pcaMethods package.
sam	Sample table including columns 'cols', 'pchs' (for data point color and shape) and 'ID' (to label data points) 'Group' (to split cols for legend) 'MP' (to adjust point size).
g	Can be a factor vector of length=nrow(sam) and will influence legend and 'medsd'.
medsd	Calculate mean and sd for groups and overlay PCA plot with this information.
text.col	Data points may be overlaid by textual information, e.g. sample ID and 'text.col' specifies the column name of 'sam' to use for this purpose.
legend.x	Position of a legend or NULL to omit it.
comm	Will print commentary text to the bottom right of the plot (can be a character vector).

Details

See examples.

Value

A vector fo similar length as input but with various name components removed.

Examples

# load raw data and sample description
raw <- MetabolomicsBasics::raw
sam <- MetabolomicsBasics::sam

# calculate pca Result using pcaMethods and plot
pca_res <- pcaMethods::pca(raw, method = "rnipals", scale = c("none", "pareto", "uv")[2])
PlotMetabolitePCA(pca_res = pca_res, sam = sam, g = sam$GT)
# plot without legend and Group means instead
PlotMetabolitePCA(
  pca_res = pca_res, sam = sam, g = sam$GT, legend.x = NULL, text.col = NULL,
  medsd = TRUE, comm = LETTERS[1:4]
)

# readjust symbols before plotting
sam$Group <- interaction(sam$Origin, sam$Class, sep = "_")
sam[, c("cols", "pchs")] <- AdjustSymbols(cols = sam$Group, pchs = sam$Group)
PlotMetabolitePCA(pca_res = pca_res, sam = sam, g = sam$Group)

MetabolomicsBasics documentation built on Nov. 2, 2023, 5:07 p.m.