bootstrapCompartments {compartmap} | R Documentation |
Non-parametric bootstrapping of compartments and summarization of bootstraps/compute confidence intervals
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 )
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 |
Compartment estimates with summarized bootstraps and confidence intervals
# this needs a good example