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 asbplapply
. 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 (seeMulticoreParam
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