Scaffold function around easypar to run workflows in parallel by chromosome

A scaffold function to be used within other complex workflow functions that provides easy API to easypar functionality and executes a function in parallel by chromosome

The scaffold takes a function where the input can be subset by chromosome and the expected output is either a data.table or GenomicRanges object

Usage

chrompar(
  par_function,
  par_chromosomes,
  ...,
  run_in_par = T,
  par_cpus = NULL,
  par_packages = NULL
)

Arguments

par_function

The function that will be executed in parallel by chromosome, written as the function name without the () a the end

par_chromosomes

The set of chromosomes to execute in parallel, non-duplicated values and can be any chromosomes as long as present in input data

...

The input parameters that will be passed to par_function for execution, these must be provided in the order expected by par_function

run_in_par

Run the jobs in parallel and not sequentially, default: TRUE

par_cpus

Number of CPUs to use for parallel execution, easypar will safeguard against using all available CPUs

par_packages

Vector of character strings designating special packages needed for executing the par_function

Value

GenomicRanges object with properly sorted genomic coordinates

Examples

# Run as part of the `get_fragcounter_segmentation()` workflow using
# `get_cbs_per_chromosome()` as the par_function
# final_cbs_segmentation <- chrompar(
# par_function = get_cbs_per_chromosome,
# par_chromosomes = chrom_iter_list,
# par_cpus = threads,
# seqnames_nona, rdp_cov_nona, start_nona, sample_id)