Samples score plots for single-omics PCA

Produces a pairwise samples score plot for the PCA run on each omics dataset, using GGally::ggpairs().

Usage

plot_samples_coordinates_pca(pca_result, pcs = NULL, datasets = NULL, ...)

Arguments

pca_result

List of PCA results on each of the datasets, each computed with the run_pca() function.

pcs

Integer vector or named list of integer vectors, the principal components to display for each dataset. If integer vector (e.g. 1:5), will be used for all datasets. Alternatively, a different set of PCs can be specified through a named list (e.g. list('snps' = 1:4, 'rnaseq' = 1:5)). The length of the list must match the number of datasets to be displayed, and the names must match the dataset names. Default value is NULL, i.e. all principal components will be plotted for each dataset.

datasets

Optional, character vector of datasets for which the plots should be created.

...

Other arguments passed to plot_samples_score().

Value

A list of ggmatrix plots (or a single ggmatrix plot if pcs has length 1).

Examples

if (FALSE) { # \dontrun{
## Default: plotting all PCs for all datasets
plot_samples_coordinates_pca(pca_result)

## Plotting only the first 3 PCs for each dataset
plot_samples_coordinates_pca(
  pca_result,
  pcs = 1:3
)

## Plotting the first 3 PCs for the genomics dataset, 4 PCs for the
## transcriptomics dataset, 5 PCs for the metabolomics dataset
plot_samples_coordinates_pca(
  pca_result,
  pcs = list(
    "snps" = 1:3,
    "rnaseq" = 1:4,
    "metabolome" = 1:5
  )
)

## Plotting the first 3 PCs for the genomics and transcriptomics datasets
plot_samples_coordinates_pca(
  pca_result,
  pcs = 1:3,
  datasets = c("snps", "rnaseq")
)

# Plotting the first 3 PCs for the genomics dataset and 4 PCs for the
## transcriptomics dataset (no plot for the metabolomics dataset)
plot_samples_coordinates_pca(
  pca_result,
  pcs = list(
    "snps" = 1:3,
    "rnaseq" = 1:4
  ),
  datasets = c("snps", "rnaseq")
)
} # }