Run A PCA

runPCA()

Runs a Principal Component Analysis (PCA).

runPCA(
    gobject,
    expression_values = c("normalized", "scaled", "custom"),
    reduction = c("cells", "genes"),
    name = "pca",
    genes_to_use = "hvg",
    return_gobject = TRUE,
    center = TRUE,
    scale_unit = TRUE,
    ncp = 100,
    method = c("irlba", "factominer"),
    rev = FALSE,
    set_seed = TRUE,
    seed_number = 1234,
    verbose = TRUE,
    ...
)

Arguments

gobject

giotto object

expression_values

expression values to use

reduction

cells or genes

name

arbitrary name for PCA run

genes_to_use

subset of genes to use for PCA

return_gobject

boolean: return giotto object (default = TRUE)

center

center data first (default = TRUE)

scale_unit

scale features before PCA (default = TRUE)

ncp

number of principal components to calculate

method

which implementation to use

rev

do a reverse PCA

set_seed

use of seed

seed_number

seed number to use

verbose

verbosity of the function

…

additional parameters for PCA (see Details)

Value

Giotto object with updated PCA dimension reduction.

Details

See prcomp_irlba() and PCA for more information about other parameters.

  • genes_to_use = NULL: will use all genes from the selected matrix

  • genes_to_use = <hvg name>: can be used to select a column name of highly variable genes, created by (see calculateHVG()).

  • genes_to_use = c('geneA', 'geneB', ...): will use all manually provided genes

Examples

data(mini_giotto_single_cell)

# run PCA
mini_giotto_single_cell <- runPCA(gobject = mini_giotto_single_cell,
              center = TRUE, scale_unit = TRUE)
#> hvg  was found in the gene metadata information and will be used to select highly variable genes #> Warning: ncp >= minimum dimension of x, will be set to minimum dimension of x - 1
#> Warning: You're computing too large a percentage of total singular values, use a standard svd instead.#> Warning: did not converge--results might be invalid!; try increasing work or maxit
#>
#>   pca  has already been used, will be overwritten
# plot PCA results
plotPCA(mini_giotto_single_cell)
runPCA runPCA