getArrayABsignal: Estimate A/B compartments from methylation array data

In biobenkj/compartmentalizer: Higher-order chromatin domain inference in single samples from methylation arrays and single cells from scRNA-seq and scATAC-seq

Estimate A/B compartments from methylation array data

Description

getArrayABsignal returns estimated A/B compartments from methylation array data.

Usage

getArrayABsignal(
  obj,
  res = 1e+06,
  parallel = TRUE,
  chr = NULL,
  targets = NULL,
  preprocess = TRUE,
  cores = 2,
  bootstrap = TRUE,
  num.bootstraps = 1000,
  genome = c("hg19", "hg38", "mm9", "mm10"),
  other = NULL,
  array.type = c("hm450", "EPIC"),
  group = FALSE,
  boot.parallel = TRUE,
  boot.cores = 2
)

Arguments

obj	Input SummarizedExperiment object
res	Compartment resolution in bp
parallel	Whether to run samples in parallel
chr	What chromosome to work on (leave as NULL to run on all chromosomes)
targets	Samples/cells to shrink towards
preprocess	Whether to preprocess the arrays prior to compartment inference
cores	How many cores to use when running samples in parallel
bootstrap	Whether we should perform bootstrapping of inferred compartments
num.bootstraps	How many bootstraps to run
genome	What genome to work on ("hg19", "hg38", "mm9", "mm10")
other	Another arbitrary genome to compute compartments on
array.type	What type of array is this ("hm450", "EPIC")
group	Whether to treat this as a group set of samples
boot.parallel	Whether to run the bootstrapping in parallel
boot.cores	How many cores to use for the bootstrapping

Value

A RaggedExperiment of inferred compartments

Examples

data("meth_array_450k_chr14", package = "compartmap")
array_compartments <- getArrayABsignal(array.data.chr14, parallel=FALSE, chr="chr14", bootstrap=FALSE, genome="hg19", array.type="hm450")

biobenkj/compartmentalizer documentation built on Oct. 13, 2023, 5:26 p.m.