import-functions: Import basepair-resolution files
In BRGenomics: Tools for the Efficient Analysis of High-Resolution Genomics Data

Description Usage Arguments Details Value Author(s) See Also Examples

Import functions for plus/minus pairs of bigWig or bedGraph files.

import_bigWig(
  plus_file = NULL,
  minus_file = NULL,
  genome = NULL,
  keep.X = TRUE,
  keep.Y = TRUE,
  keep.M = FALSE,
  keep.nonstandard = FALSE,
  makeBRG = TRUE,
  ncores = getOption("mc.cores", 2L)
)

import_bedGraph(
  plus_file = NULL,
  minus_file = NULL,
  genome = NULL,
  keep.X = TRUE,
  keep.Y = TRUE,
  keep.M = FALSE,
  keep.nonstandard = FALSE,
  ncores = getOption("mc.cores", 2L)
)

`plus_file, minus_file`	Paths for strand-specific input files, or a vector of such paths. If vectors are given, the user should take care that the orders match!
`genome`	Optional string for UCSC reference genome, e.g. "hg38". If given, non-standard chromosomes are trimmed, and options for sex and mitochondrial chromosomes are applied.
`keep.X, keep.Y, keep.M, keep.nonstandard`	Logicals indicating which non-autosomes should be kept. By default, sex chromosomes are kept, but mitochondrial and non-standard chromosomes are removed.
`makeBRG`	If `TRUE` (the default), the output ranges are made single-width using `makeGRangesBRG`
`ncores`	Number of cores to use, if importing multiple objects simultaneously.

For import_bigWig, the output GRanges is formatted by makeGRangesBRG, such that all ranges are disjoint and have width = 1, and the score is single-base coverage, i.e. the number of reads for each position.

import_bedGraph is useful for when both 5'- and 3'-end information is to be maintained for each sequenced molecule. For this purpose, one use bedGraphs to store entire reads, with the score representing the number of reads sharing identical 5' and 3' ends. However, import_bedGraph doesn't modify the information in the bedGraph files. If the bedGraph file represents basepair-resolution coverage data, then users can coerce it to a basepair-resolution GRanges object by using getStrandedCoverage followed by makeGRangesBRG.

Imports a GRanges object containing base-pair resolution data, with the score metadata column indicating the number of reads represented by each range.

Mike DeBerardine

tidyChromosomes, rtracklayer::import

#--------------------------------------------------#
# Import PRO-seq bigWigs -> coverage of 3' bases
#--------------------------------------------------#

# get local address for included bigWig files
p.bw <- system.file("extdata", "PROseq_dm6_chr4_plus.bw",
                    package = "BRGenomics")
m.bw <- system.file("extdata", "PROseq_dm6_chr4_minus.bw",
                    package = "BRGenomics")

# import bigWigs (not supported on windows)
if (.Platform$OS.type == "unix") {
    PROseq <- import_bigWig(p.bw, m.bw, genome = "dm6")
    PROseq
}


#--------------------------------------------------#
# Import PRO-seq bedGraphs -> whole reads (matched 5' and 3' ends)
#--------------------------------------------------#

# get local address for included bedGraph files
p.bg <- system.file("extdata", "PROseq_dm6_chr4_plus.bedGraph",
                    package = "BRGenomics")
m.bg <- system.file("extdata", "PROseq_dm6_chr4_minus.bedGraph",
                    package = "BRGenomics")

# import bedGraphs
PROseq_paired <- import_bedGraph(p.bg, m.bg, genome = "dm6")
PROseq_paired