import_bam {BRGenomics} | R Documentation

## Import bam files

### Description

Import single-end or paired-end bam files as GRanges objects, with various processing options. It is highly recommend to index the BAM file first.

### Usage

    import_bam(
      file,
      mapq = 20,
      revcomp = FALSE,
      shift = 0L,
      trim.to = c("whole", "5p", "3p", "center"),
      ignore.strand = FALSE,
      field = "score",
      paired_end = NULL,
      yieldSize = NA,
      ncores = 1
    )

    import_bam_PROseq(
      file,
      mapq = 20,
      revcomp = TRUE,
      shift = -1L,
      trim.to = "3p",
      ignore.strand = FALSE,
      field = "score",
      paired_end = NULL,
      yieldSize = NA,
      ncores = 1
    )

    import_bam_PROcap(
      file,
      mapq = 20,
      revcomp = FALSE,
      shift = 0L,
      trim.to = "5p",
      ignore.strand = FALSE,
      field = "score",
      paired_end = NULL,
      yieldSize = NA,
      ncores = 1
    )

    import_bam_ATACseq(
      file,
      mapq = 20,
      revcomp = FALSE,
      shift = c(4, -5),
      trim.to = "whole",
      ignore.strand = TRUE,
      field = "score",
      paired_end = TRUE,
      yieldSize = NA,
      ncores = 1
    )

### Arguments

`file` | Path of a bam file, or a vector of paths.
`mapq` | Filter reads by a minimum MAPQ score. This is the correct way to filter multi-aligners.
`revcomp` | Logical indicating if aligned reads should be reverse-complemented.
`shift` | Either an integer giving the number of bases by which to shift the entire read upstream or downstream, or a pair of integers indicating shifts to be applied to the 5' and 3' ends of the reads, respectively. Shifting is strand-specific, with negative numbers shifting the reads upstream, and positive numbers shiftem them downstream. This option is applied after the `revcomp`, but before `trim.to` and `ignore.strand` options are applied.
`trim.to` | Option for selecting specific bases from the reads, applied after the `revcomp` and `shift` options. By default, the entire read is maintained. Other options are to take only the 5' base, only the 3' base, or the only the center base of the read.
`ignore.strand` | Logical indicating if the strand information should be discarded. If `TRUE`, strand information is discarded after `revcomp`, `trim.to`, and `shift` options are applied.
`field` | Metadata field name to use for readcounts, usually "score". If set to `NULL`, identical reads (or identical positions if `trim.to` options applied) are not combined, and the length of the output GRanges will be equal to the number of input reads.
`paired_end` | Logical indicating if reads should be treated as paired end reads. When set to `NULL` (the default), the first 100k reads are checked.
`yieldSize` | The number of bam file records to process simultaneously, e.g. the "chunk size". Setting a higher chunk size will use more memory, which can increase speed if there is enough memory available. If chunking is not necessary, set to `NA`.
`ncores` | Number of cores to use for importing bam files. Currently, multicore is only implemented for simultaneously importing multiple bam files. For smaller datasets or machines with higher memory, this can increase performance, but can otherwise lead to substantial performance penalties.

### Value

A GRanges object.

### Author(s)

Mike DeBerardine

### References

Hojoong Kwak, Nicholas J. Fuda, Leighton J. Core, John T. Lis (2013). Precise Maps of RNA Polymerase Reveal How Promoters Direct Initiation and Pausing. Science 339(6122): 950–953. https://doi.org/10.1126/science.1229386

Jason D. Buenrostro, Paul G. Giresi, Lisa C. Zaba, Howard Y. Chang, William J. Greenleaf (2013). Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, dna-binding proteins and nucleosome position. Nature Methods 10: 1213–1218. https://doi.org/10.1038/nmeth.2688

### Examples

    # get local address for included bam file
    ps.bam <- system.file("extdata", "PROseq_dm6_chr4.bam",
                          package = "BRGenomics")

    #--------------------------------------------------#
    # Import entire reads
    #--------------------------------------------------#

    # Note that PRO-seq reads are sequenced as reverse complement
    import_bam(ps.bam, revcomp = TRUE, paired_end = FALSE)

    #--------------------------------------------------#
    # Import entire reads, 1 range per read
    #--------------------------------------------------#

    import_bam(ps.bam, revcomp = TRUE, field = NULL,
               paired_end = FALSE)

    #--------------------------------------------------#
    # Import PRO-seq reads at basepair-resolution
    #--------------------------------------------------#

    # the typical manner to import PRO-seq data:
    import_bam(ps.bam, revcomp = TRUE, trim.to = "3p",
               paired_end = FALSE)

    #--------------------------------------------------#
    # Import PRO-seq reads, removing the run-on base
    #--------------------------------------------------#

    # the best way to import PRO-seq data; removes the
    # most 3' base, which was added in the run-on
    import_bam(ps.bam, revcomp = TRUE, trim.to = "3p",
               shift = -1, paired_end = FALSE)

    #--------------------------------------------------#
    # Import 5' ends of PRO-seq reads
    #--------------------------------------------------#

    # will include bona fide TSSes as well as hydrolysis products
    import_bam(ps.bam, revcomp = TRUE, trim.to = "5p",
               paired_end = FALSE)

[Package BRGenomics version 1.4.0 Index]