scCompartments: Estimate A/B compartments from single-cell sequencing data

In biobenkj/compartmap: 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 single-cell sequencing data

Description

scCompartments returns estimated A/B compartments from sc-seq data.

Usage

scCompartments(
  obj,
  res = 1e+06,
  parallel = FALSE,
  chr = NULL,
  targets = NULL,
  cores = 2,
  bootstrap = TRUE,
  num.bootstraps = 100,
  genome = c("hg19", "hg38", "mm9", "mm10"),
  group = FALSE,
  assay = c("atac", "rna")
)

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
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")
group	Whether to treat this as a group set of samples
assay	What type of single-cell assay is the input data ("atac" or "rna")

Value

A RaggedExperiment of inferred compartments

Examples

data("k562_scrna_chr14", package = "compartmap")
sc_compartments <- scCompartments(k562_scrna_chr14, parallel=FALSE, chr="chr14", bootstrap=FALSE, genome="hg19")

biobenkj/compartmap documentation built on Oct. 18, 2023, 11:11 a.m.