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Create phenoclasses matrix for cell type deconvolution

Source: R/create_phenoclasses.R
create_phenoclasses.Rd

Generates a phenotype classification matrix from sample data for use in cell type deconvolution workflows. This matrix maps samples to their respective cell types.

Usage

create_phenoclasses(
  data,
  mapping_rules,
  verbose = FALSE,
  return_format = c("tibble", "matrix")
)

Arguments

data

A numeric matrix of pure cell type profiles with genes as row names and samples as columns. Column names should contain identifiers that can be mapped to cell types.

mapping_rules

Either: 1. A named list where names are cell type labels and values are regular expression patterns used to match sample column names (e.g., list("CD8+ T cells" = "CD8", "Monocytes" = "Mono")), OR 2. A character vector with the same length and order as colnames(data), directly specifying the cell type for each sample.

verbose

Logical. If TRUE, displays additional messages during processing.

return_format

A string specifying the return format: "matrix" or "tibble" (default).

Value

If return_format is "matrix", a numeric matrix with cell type groups as rows and samples as columns. If return_format is "tibble", a tibble with a "cell_type" column and columns for each sample.

Details

The function is particularly useful for preparing reference data for signature matrix generation using CIBERSORTx. Each cell in the output is encoded as:

  • 0 for 'Unknown' mappings

  • 1 if the sample belongs to the cell type in that row

  • 2 if the sample belongs to a different cell type

See also

create_signature_matrix which uses the phenoclasses matrix to generate a cell type signature matrix.

Examples

if (FALSE) { # \dontrun{
# Example using a named list of regex patterns
pure_samples <- readRDS(system.file("extdata", "pure_samples_matrix.rds",
                                     package = "proteoDeconv"))

mapping_rules <- list(
  "CD8+ T cells" = "CD8",
  "Monocytes" = "Mono"
)

phenoclasses1 <- create_phenoclasses(
  data = pure_samples,
  mapping_rules = mapping_rules,
  verbose = TRUE
)

# Example using a character vector of direct cell type assignments
cell_types <- c("CD8+ T cells", "CD8+ T cells", "Monocytes", "Monocytes", "Unknown")
phenoclasses2 <- create_phenoclasses(
  data = pure_samples,
  mapping_rules = cell_types,
  verbose = TRUE
)
} # }