shrinkBins: Employ an eBayes shrinkage approach for bin-level estimates...

In JordanVeldboom/compartmap: A/B compartment inference from ATAC-seq and methylation array data

Description

shrinkBins returns shrunken bin-level estimates

Usage

shrinkBins(
  x,
  original.x,
  prior.means = NULL,
  chr = NULL,
  res = 1000000,
  targets = NULL,
  assay = c("array", "atac", "bisulfite"),
  genome = c("hg19", "hg38", "mm9", "mm10")
)

Arguments

x	Input SummarizedExperiment object
original.x	Full sample set SummarizedExperiment object
prior.means	The means of the bin-level prior distribution
chr	The chromosome to operate on
res	Resolution to perform the binning
targets	The column/sample/cell names to shrink towards
assay	What assay type this is ("array", "atac", "bisulfite")
genome	What genome are we working with ("hg19", "hg38", "mm9", "mm10")

Details

This function computes shrunken bin-level estimates using a James-Stein estimator, reformulated as an eBayes procedure

Value

A list object to pass to getCorMatrix

Examples

data("meth_array_450k_chr14", package = "compartmap")
#impute to remove NAs
imputed.array <- imputeKNN(array.data.chr14, assay = "array")
#get the shrunken binned M-values
shrunken.bin.array <- shrinkBins(imputed.array, chr = "chr14", assay = "array")

JordanVeldboom/compartmap documentation built on July 3, 2020, 6:32 p.m.