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Calculates PCA on Pearson residuals for meta cells

rs_mc_pca_residuals.Rd

[Experimental] In-memory version of rs_sc_pca_residuals(). As there, clr and normalise_variance must both be FALSE.

Usage

rs_mc_pca_residuals(
  sparse_data,
  residual_fit,
  no_pcs,
  pca_params,
  gene_indices,
  seed,
  verbose
)

Arguments

sparse_data

A named list that needs to have data, indptr, indices, nrow, ncol and cs_type. Shape is (metacells, genes). Pass raw counts.

residual_fit

List. A fit from rs_mc_fit_residuals().

no_pcs

Integer. Number of PCs to calculate.

pca_params

Named list. Contains the parameters to use for this PCA run.

gene_indices

Integer vector. The gene indices to use. (0-indexed!)

seed

Integer. Random seed for the randomised SVD.

verbose

Integer. 0L - quiet; 1L - normal verbosity; 2L - detailed verbosity.

Value

A list with the following items

  • scores - The samples projected on the PCA space.

  • loadings - The loadings of the features for the PCA.

  • singular_values - The singular values for the PCA.