bootstrapCompartments {compartmap} | R Documentation

## Non-parametric bootstrapping of compartments and summarization of bootstraps/compute confidence intervals

### Description

Non-parametric bootstrapping of compartments and summarization of bootstraps/compute confidence intervals

### Usage

    bootstrapCompartments(
      obj,
      original.obj,
      bootstrap.samples = 1000,
      chr = "chr14",
      assay = c("rna", "atac"),
      parallel = TRUE,
      cores = 2,
      targets = NULL,
      res = 1e+06,
      genome = c("hg19", "hg38", "mm9", "mm10"),
      q = 0.95,
      svd = NULL,
      group = FALSE,
      bootstrap.means = NULL
    )

### Arguments

`obj` | List object of computed compartments for a sample with 'pc' and 'gr' as elements
`original.obj` | The original, full input SummarizedExperiment of all samples/cells
`bootstrap.samples` | How many bootstraps to run
`chr` | Which chromosome to operate on
`assay` | What sort of assay are we working on
`parallel` | Whether to run the bootstrapping in parallel
`cores` | How many cores to use for parallel processing
`targets` | Targets to shrink towards
`res` | The compartment resolution
`genome` | What genome are we working on
`q` | What sort of confidence intervals are we computing (e.g. 0.95 for 95 percentCI)
`svd` | The original compartment calls as a GRanges object
`group` | Whether this is for group-level inference
`bootstrap.means` | Pre-computed bootstrap means matrix

### Value

Compartment estimates with summarized bootstraps and confidence intervals

### Examples

    # this needs a good example

[Package compartmap version 1.10.0 Index]