Get feature coefficients

Get feature coefficients from ICP models.

Usage

GetFeatureCoefficients.SingleCellExperiment(
  object,
  icp.run = NULL,
  icp.round = NULL
)

# S4 method for class 'SingleCellExperiment'
GetFeatureCoefficients(object, icp.run = NULL, icp.round = NULL)

Arguments

object

An object of SingleCellExperiment class with ICP cell cluster probability tables saved in metadata(object)$coralysis$joint.probability. After running RunParallelDivisiveICP.

icp.run

ICP run(s) to retrieve from metadata(object)$coralysis$joint.probability. By default NULL, i.e., all are retrieved. Specify a numeric vector to retrieve a specific set of tables.

icp.round

ICP round(s) to retrieve from metadata(object)$coralysis$joint.probability. By default NULL, i.e., all are retrieved.

Value

A list of feature coefficient weights per cluster per ICP run/round.

Examples

if (FALSE) { # \dontrun{
# Import package
suppressPackageStartupMessages(library("SingleCellExperiment"))

# Import data from Zenodo
data.url <- "https://zenodo.org/records/14845751/files/pbmc_10Xassays.rds?download=1"
sce <- readRDS(file = url(data.url))

# Multi-level integration (just for highlighting purposes; use default parameters)
set.seed(123)
sce <- RunParallelDivisiveICP(object = sce, batch.label = "batch", 
                              k = 4, L = 10, C = 1, d = 0.5, 
                              train.with.bnn = FALSE, use.cluster.seed = FALSE,
                              build.train.set = FALSE, ari.cutoff = 0.1, 
                              threads = 2)

# GetFeatureCoefficients
gene_coefficients_icp_2_4 <- GetFeatureCoefficients(object = sce, 
                                                    icp.run = 2, icp.round = 4)
head(gene_coefficients_icp_2_4$icp_8)
} # }