Create a BetaHandler object for efficient beta value access

Create a new BetaHandler object that manages methylation beta values from various input formats (files, matrices, tabix, BSseq objects) with memory-efficient access patterns.

Usage

getBetaHandler(
  beta,
  array = c("450K", "27K", "EPIC", "EPICv2"),
  genome = c("hg38", "hg19", "hs1", "mm10", "mm39"),
  beta_row_names_file = NULL,
  sorted_locs = NULL,
  chrom_col = "#chrom",
  start_col = "start",
  output_prefix = NULL,
  njobs = getOption("CMEnt.njobs", .defaultNJobs())
)

Arguments

beta: Path to beta values file, or a tabix, or a beta matrix, or a BSseq object
array: Array platform type, ignored if sorted_locs or a BSseq object have been provided
genome: Reference genome version, eg. hg38 or hs1. Only human and mouse genomes are supported. Ignored if sorted_locs or a BSseq object have been provided.
beta_row_names_file: Path to row names file
sorted_locs: Data frame with genomic locations containing 'chr' and 'start' and 'end' columns, sorted by genomic position. If NULL, will be retrieved automatically using genome and array information, or extracted from BSseq object.
chrom_col: Chromosome column name in tabix file
start_col: Start position column name in tabix file
output_prefix: Prefix used for saving derived beta artifacts.
njobs: Number of parallel jobs to use when reading beta file or tabix file. Default is number of available cores minus one, up to a maximum of 8.

Value

A new BetaHandler object

Examples

loadExampleInputData("beta")
beta_matrix <- beta

beta_handler <- getBetaHandler(
    beta = beta_matrix,
    array = "450K",
    genome = "hg38"
)

beta_locs <- beta_handler$getBetaLocs()
head(beta_locs)

beta_values <- beta_handler$getBeta()
head(beta_values[, 1:5])