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Automorphisms estimated on a pairwise or a MSA alignment can be grouped by ranges which inherits from GRanges-class or a GRanges-class.

Usage

automorphismByRanges(x, ...)

# S4 method for Automorphism
automorphismByRanges(x)

# S4 method for AutomorphismList
automorphismByRanges(
  x,
  min.len = 0L,
  num.cores = multicoreWorkers(),
  tasks = 0L,
  verbose = TRUE
)

Arguments

x

An AutomorphismList-class object returned by function automorphisms.

...

Not in use.

min.len

Minimum length of a range to be reported.

num.cores, tasks

Integers. Argument num.cores denotes the number of cores to use, i.e. at most how many child processes will be run simultaneously (see bplapply function from BiocParallel package). Argument tasks denotes the number of tasks per job. value must be a scalar integer >= 0L. In this documentation a job is defined as a single call to a function, such as bplapply. A task is the division of the \(X\) argument into chunks. When tasks == 0 (default), \(X\) is divided as evenly as possible over the number of workers (see MulticoreParam from BiocParallel package).

verbose

logic(1). If TRUE, enable progress bar.

Value

A GRanges-class or a GRangesList-class. Each GRanges-class object with a column named cube, which carries the type of cube automorphims.

Examples

## Load dataset
data("autm", package = "GenomAutomorphism")

automorphismByRanges(x = autm[c(1, 4)])
#> GRanges object with 1 range and 1 metadata column:
#>       seqnames    ranges strand |        cube
#>          <Rle> <IRanges>  <Rle> | <character>
#>   [1]        1       1-4      + |        ACGT
#>   -------
#>   seqinfo: 1 sequence from an unspecified genome; no seqlengths