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Query lines from a tabixed bedfile

Source: R/tabix.R
tabix.Rd

Query lines from a tabixed bedfile

Usage

tabix(
  bedfiles,
  regions,
  aligner = "biscuit",
  col.names = NULL,
  raw = FALSE,
  nthreads = NULL
)

Arguments

bedfiles

The bedfiles to be queried

regions

A vector, data frame or GenomicRanges of genomic regions. See details.

aligner

The aligner used to produce the BED files - one of "biscuit", "bismark", "bsbolt". Will set the result data.table's column names based on this argument.

col.names

A vector of column names for the result data.table. Set if your bedfile is not from the supported aligners or is a general bedfile.

raw

Set true to give a named list of raw strings from the regions in the style of Rsamtools::scanTabix instead of a data.table

nthreads

Set number of threads to use overriding the "iscream.threads" option. See ?set_threads for more information.

Value

A data.table

Details

Query method

'iscream has two methods to query records from BED files:

  • the tabix shell executable: fast since its output can be redirected to a file (which data.table::fread() can then read) instead of having to allocate memory and store it during the query

  • iscream's tabix implementation, based on the tabix executable using htslib, but slower on large queries since it stores the records as they are found instead of writing to a file. However it's able to store each regions records independently instead of in a single file and is used in query_all() and summarize_regions().

When iscream is attached, it checks that the tabix executable is available with Sys.which() and, if available, sets options("tabix.method" = "shell"). tabix() then uses the tabix executable to make queries, except if raw = TRUE. If tabix is not found, iscream uses its tabix implementation. To use only iscream's tabix implementation, set options("tabix.method" = "htslib").

Input region formats

The input regions may be string vector in the form "chr:start-end", a dataframe with "chr", "start" and "end" columns or a GRanges object. If the input is a GRanges, the output will also be GRanges with any associated metadata columns (joined onto the result using GenomicRanges::findOverlaps())

Examples

bedfiles <- system.file("extdata", package = "iscream") |>
  list.files(pattern = "[a|b|c|d].bed.gz$", full.names = TRUE)
regions <- c("chr1:1-6", "chr1:7-10", "chr1:11-14")
tabix(bedfiles[1], regions, col.names = c("chr", "start", "end", "beta", "coverage"))
#>       chr start   end  beta coverage
#>    <char> <int> <int> <num>    <int>
#> 1:   chr1     1     2   1.0        1
#> 2:   chr1     3     4   1.0        1
#> 3:   chr1     5     6   0.0        2
#> 4:   chr1     7     8   0.0        1
#> 5:   chr1     9    10   0.5        2
#> 6:   chr1    11    12   1.0        2
#> 7:   chr1    13    14   1.0        3