| IRanges-class {IRanges} | R Documentation |
The IRanges class is a simple implementation of the Ranges container where 2 integer vectors of the same length are used to store the start and width values. See the Ranges virtual class for a formal definition of Ranges 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 Ranges objects for the definition and properties of "normal" Ranges objects.
See ?`IRanges-constructor`.
ranges(x, use.names=FALSE, use.mcols=FALSE): Squeeze the ranges
out of Ranges 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 a Ranges
object, logical vector, 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) Combining IRanges
objects is straightforward when they do not have any metadata columns.
If only one of the IRanges object has metadata columns, then
the corresponding metadata columns are attached to the other
IRanges object and set to NA.
When multiple IRanges object have their own
metadata columns, the user must ensure that each such
linkS4class{DataFrame} have identical layouts to each other
(same columns defined), in order for the combination to be successful,
otherwise an error will be thrown. The user can call
c(x, ..., ignore.mcols=TRUE) in order to combine
IRanges objects with differing sets of metadata columns,
which will result in the combined object having NO metadata columns.
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 Ranges objects work on IRanges objects.
## See ?Ranges for some examples.
## Also see ?`IRanges-utils` and ?`setops-methods` for additional
## operations on IRanges objects.
## Combining 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)