ssvFetchBam: Iterates a character vector (ideally named) and calls...
In seqsetvis: Set Based Visualizations for Next-Gen Sequencing Data

Description Usage Arguments Details Value Examples

ssvFetchBam iteratively calls fetchWindowedBam.single. See ssvFetchBam.single for more info.

ssvFetchBam(
  file_paths,
  qgr,
  unique_names = NULL,
  names_variable = "sample",
  file_attribs = NULL,
  win_size = 50,
  win_method = c("sample", "summary")[1],
  summary_FUN = stats::weighted.mean,
  fragLens = "auto",
  target_strand = c("*", "+", "-", "both")[1],
  flip_strand = FALSE,
  anchor = c("left", "left_unstranded", "center", "center_unstranded")[3],
  return_data.table = FALSE,
  max_dupes = Inf,
  splice_strategy = c("none", "ignore", "add", "only", "splice_count")[1],
  n_cores = getOption("mc.cores", 1),
  n_region_splits = 1,
  return_unprocessed = FALSE,
  force_skip_centerFix = FALSE,
  ...
)

`file_paths`	character vector of file_paths to load from. Alternatively, file_paths can be a data.frame or data.table whose first column is a character vector of paths and additial columns will be used as metadata.
`qgr`	Set of GRanges to query. For valid results the width of each interval should be identical and evenly divisible by `win_size`.
`unique_names`	names to use in final data.table to designate source bigwig. Default is 'sample'
`names_variable`	The column name where unique_names are stored.
`file_attribs`	optional data.frame/data.table with one row per item in file paths. Each column will be a variable added to final tidy output.
`win_size`	The window size that evenly divides widths in `qgr`.
`win_method`	character. one of c("sample", "summary"). Determines if `viewGRangesWinSample_dt` or `viewGRangesWinSummary_dt` is used to represent each region in qgr.
`summary_FUN`	function. only relevant if win_method is "summary". passed to `viewGRangesWinSummary_dt`.
`fragLens`	numeric. The fragment length to use to extend reads. The default value "auto" causes an automatic calculation from 100 regions in qgr. NA causes no extension of reads to fragment size.
`target_strand`	character. One of c("", "+", "-"). Controls filtering of reads by strand. Default of "" combines both strands.
`flip_strand`	boolean. if TRUE strands are flipped.
`anchor`	character, one of c("center", "center_unstranded", "left", "left_unstranded")
`return_data.table`	logical. If TRUE the internal data.table is returned instead of GRanges. Default is FALSE.
`max_dupes`	numeric >= 1. duplicate reads by strandd start position over this number are removed, Default is Inf.
`splice_strategy`	character, one of c("none", "ignore", "add", "only", "splice_count"). Default is "none" and spliced alignment are asssumed not present. fragLen must be NA for any other value to be valid. "ignore" will not count spliced regions. add" counts spliced regions along with others, "only" will only count spliced regions and ignore others.
`n_cores`	integer number of cores to use. Uses mc.cores option if not supplied.
`n_region_splits`	integer number of splits to apply to qgr. The query GRanges will be split into this many roughly equal parts for increased parallelization. Default is 1, no split.
`return_unprocessed`	boolean. if TRUE returns read alignment in data.table. Default is FALSE.
`force_skip_centerFix`	boolean, if TRUE all query ranges will be used "as is". This is already the case by default if win_method == "summary" but may have applications where win_method == "sample".
`...`	passed to Rsamtools::ScanBamParam()

if qgr contains the range chr1:1-100 and win_size is 10, values from positions chr1 5,15,25...85, and 95 will be retrieved from bw_file

A tidy formatted GRanges (or data.table if specified) containing fetched values.

if(Sys.info()['sysname'] != "Windows"){
library(GenomicRanges)
bam_f = system.file("extdata/test.bam",
    package = "seqsetvis", mustWork = TRUE)
bam_files = c("a" = bam_f, "b" = bam_f)
qgr = CTCF_in_10a_overlaps_gr[1:5]
bw_gr = ssvFetchBam(bam_files, qgr, win_size = 10)
bw_gr2 = ssvFetchBam(as.list(bam_files), qgr, win_size = 10)

bw_dt = ssvFetchBam(bam_files, qgr, win_size = 10,
    return_data.table = TRUE)
}