getCompartments {compartmap} | R Documentation |
getCompartments
returns estimated A/B compartments from ATAC-seq and methylation array data
getCompartments(obj, type = c("atac", "array"), res = 1e+06, parallel = FALSE, chrs = "chr1", genome = "hg19", targets = NULL, run_examples = FALSE, ...)
obj |
The object with which to perform compartment inference |
type |
The type of data that obj represents (e.g. atac or array) |
res |
Resolution of compartments in base pairs (default is 1e6) |
parallel |
Should the estimates be done in parallel (default is FALSE) |
chrs |
Chromosomes to operate on (can be individual chromosomes, a list of chromosomes, or all) |
genome |
Genome to use (default is hg19) |
targets |
Specify samples to use as shrinkage targets |
run_examples |
Whether to run ATAC-seq and 450k example analysis |
... |
Other parameters to pass to internal functions |
This is a wrapper function to perform A/B compartment inference. Compartmentalizer implements a Stein estimator to shrink per-sample compartment estimates towards a global mean. The expected input for this function can be generated using packages like SeSAMe and ATACseeker.
A p x n matrix (samples as columns and compartments as rows) to pass to embed_compartments
library(GenomicRanges) library(SummarizedExperiment) library(Homo.sapiens) #ATAC-seq data data(bulkATAC_raw_filtered_chr14, package = "compartmap") atac_compartments <- getCompartments(filtered.data.chr14, type = "atac", parallel = FALSE, chrs = "chr14") ## Not run: #450k data data(meth_array_450k_chr14, package = "compartmap") array_compartments <- getCompartments(array.data.chr14, type = "array", parallel = FALSE, chrs = "chr14") ## End(Not run)