getBinMatrix {compartmap} | R Documentation

## Generate bins for A/B compartment estimation

### Description

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(x, genloc, chr = "chr1", chr.start = 0, chr.end = NULL,
      res = 1e+05, FUN = sum, genome = "hg19")

### Arguments

`x` | 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" or "mm10")

### Details

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

### Value

A list object to pass to getCorMatrix

### Examples

    library(GenomicRanges)
    library(Homo.sapiens)

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

[Package compartmap version 1.6.0 Index]