IRanges-class {IRanges} | R Documentation |
The IRanges class is a simple implementation of the IntegerRanges container where 2 integer vectors of the same length are used to store the start and width values. See the IntegerRanges virtual class for a formal definition of IntegerRanges objects and for their methods (all of them should work for IRanges objects).
Some subclasses of the IRanges class are: NormalIRanges, Views, etc...
A NormalIRanges object is just an IRanges object that is guaranteed to be "normal". See the Normality section in the man page for IntegerRanges objects for the definition and properties of "normal" IntegerRanges objects.
See ?`IRanges-constructor`
.
ranges(x, use.names=FALSE, use.mcols=FALSE)
: Squeeze the ranges
out of IntegerRanges object x
and return them in an IRanges
object parallel to x
(i.e. same length as x
).
as(from, "IRanges")
: Creates an IRanges instance from an
IntegerRanges derivative, or from a logical or integer vector.
When from
is a logical vector, the resulting IRanges object
contains the indices for the runs of TRUE
values.
When from
is an integer vector, the elements are either
singletons or "increase by 1" sequences.
as(from, "NormalIRanges")
: Creates a NormalIRanges instance
from a logical or integer vector. When from
is an integer vector,
the elements must be strictly increasing.
c(x, ..., ignore.mcols=FALSE)
:
Concatenate IRanges object x
and the IRanges objects in
...
together.
See ?c
in the S4Vectors package for
more information about concatenating Vector derivatives.
max(x)
:
The maximum value in the finite set of integers represented by x
.
min(x)
:
The minimum value in the finite set of integers represented by x
.
Hervé Pagès
IRanges-constructor, IRanges-utils,
intra-range-methods for intra range transformations,
inter-range-methods for inter range transformations,
showClass("IRanges") # shows (some of) the known subclasses ## --------------------------------------------------------------------- ## A. MANIPULATING IRanges OBJECTS ## --------------------------------------------------------------------- ## All the methods defined for IntegerRanges objects work on IRanges ## objects. ## See ?IntegerRanges for some examples. ## Also see ?`IRanges-utils` and ?`setops-methods` for additional ## operations on IRanges objects. ## Concatenating IRanges objects ir1 <- IRanges(c(1, 10, 20), width=5) mcols(ir1) <- DataFrame(score=runif(3)) ir2 <- IRanges(c(101, 110, 120), width=10) mcols(ir2) <- DataFrame(score=runif(3)) ir3 <- IRanges(c(1001, 1010, 1020), width=20) mcols(ir3) <- DataFrame(value=runif(3)) some.iranges <- c(ir1, ir2) ## all.iranges <- c(ir1, ir2, ir3) ## This will raise an error all.iranges <- c(ir1, ir2, ir3, ignore.mcols=TRUE) stopifnot(is.null(mcols(all.iranges))) ## --------------------------------------------------------------------- ## B. A NOTE ABOUT PERFORMANCE ## --------------------------------------------------------------------- ## Using an IRanges object for storing a big set of ranges is more ## efficient than using a standard R data frame: N <- 2000000L # nb of ranges W <- 180L # width of each range start <- 1L end <- 50000000L set.seed(777) range_starts <- sort(sample(end-W+1L, N)) range_widths <- rep.int(W, N) ## Instantiation is faster system.time(x <- IRanges(start=range_starts, width=range_widths)) system.time(y <- data.frame(start=range_starts, width=range_widths)) ## Subsetting is faster system.time(x16 <- x[c(TRUE, rep.int(FALSE, 15))]) system.time(y16 <- y[c(TRUE, rep.int(FALSE, 15)), ]) ## Internal representation is more compact object.size(x16) object.size(y16)