Generate bins for A/B compartment estimation

Generate bins across a user defined chromosome for A/B compartment estimation. A/B compartment estimation can be used for non-supported genomes if chr.end is set.

Usage

getBinMatrix(
  mat,
  genloc,
  chr = "chr1",
  chr.start = 0,
  chr.end = NULL,
  res = 100000,
  FUN = sum,
  genome = c("hg19", "hg38", "mm9", "mm10")
)

Arguments

mat

A p x n matrix where p (rows) = loci and n (columns) = samples/cells

genloc

GRanges object that contains corresponding genomic locations of the loci

chr

Chromosome to be analyzed

chr.start

Starting position (in bp) to be analyzed

chr.end

End position (in bp) to be analyzed

res

Binning resolution (in bp)

FUN

Function to be used to summarize information within a bin

genome

Genome corresponding to the input data ("hg19", "hg38", "mm9", "mm10")

Value

A list object to pass to getCorMatrix

Details

This function is used to generate a list object to be passed to getCorMatrix

Examples

library(GenomicRanges)

# Generate random genomic intervals of 1-1000 bp on chr1-22
# Modified from https://www.biostars.org/p/225520/
genome.gr <- getGenome("hg19")
random_genomic_int <- data.frame(chr = rep("chr14", 100))
random_genomic_int$start <- apply(random_genomic_int, 1, function(x) {
  round(runif(1, 0, getSeqLengths(genome.gr, chr = x)[[1]]), 0)
})
random_genomic_int$end <- random_genomic_int$start + runif(1, 1, 1000)
random_genomic_int$strand <- "*"

# Generate random counts
counts <- rnbinom(1000, 1.2, 0.4)

# Build random counts for 10 samples
count.mat <- matrix(sample(counts, nrow(random_genomic_int) * 10, replace = FALSE), ncol = 10)
colnames(count.mat) <- paste0("sample_", seq(1:10))

# Bin counts
bin.counts <- getBinMatrix(
  count.mat,
  makeGRangesFromDataFrame(random_genomic_int),
  chr = "chr14",
  genome = "hg19"
)
#> 1074 bins created...