GenomicRanges (version 1.24.1)

inter-range-methods: Inter range transformations of a GRanges or GRangesList object

Description

This man page documents inter range transformations of a GenomicRanges object (i.e. of an object that belongs to the GenomicRanges class or one of its subclasses, this includes for example GRanges objects), or a GRangesList object.

See ?`intra-range-methods` and ?`inter-range-methods` in the IRanges package for a quick introduction to intra range and inter range transformations.

See ?`intra-range-methods` for intra range transformations of a GenomicRanges object or GRangesList object.

Usage

"range"(x, ..., ignore.strand=FALSE, na.rm=FALSE)
"range"(x, ..., ignore.strand=FALSE, na.rm=FALSE)
"reduce"(x, drop.empty.ranges=FALSE, min.gapwidth=1L, with.revmap=FALSE, with.inframe.attrib=FALSE, ignore.strand=FALSE)
"reduce"(x, drop.empty.ranges=FALSE, min.gapwidth=1L, with.inframe.attrib=FALSE, ignore.strand=FALSE)
"gaps"(x, start=1L, end=seqlengths(x))
"disjoin"(x, ignore.strand=FALSE)
"disjoin"(x, ignore.strand=FALSE)
"isDisjoint"(x, ignore.strand=FALSE)
"isDisjoint"(x, ignore.strand=FALSE)
"disjointBins"(x, ignore.strand=FALSE)

Arguments

x

A GenomicRanges object.

drop.empty.ranges, min.gapwidth, with.revmap, with.inframe.attrib, start, end

See ?`inter-range-methods` in the IRanges package.

ignore.strand

TRUE or FALSE. Whether the strand of the input ranges should be ignored or not. See details below.

...

For range, additional GenomicRanges objects to consider. Ignored otherwise.

na.rm

Ignored.

Details

On a GRanges object range returns an object of the same type as x containing range bounds for each distinct (seqname, strand) pairing. The names (names(x)) and the metadata columns in x are dropped.

reduce returns an object of the same type as x containing reduced ranges for each distinct (seqname, strand) pairing. The names (names(x)) and the metadata columns in x are dropped. See ?reduce for more information about range reduction and for a description of the optional arguments.

gaps returns an object of the same type as x containing complemented ranges for each distinct (seqname, strand) pairing. The names (names(x)) and the columns in x are dropped. For the start and end arguments of this gaps method, it is expected that the user will supply a named integer vector (where the names correspond to the appropriate seqlevels). See ?gaps for more information about range complements and for a description of the optional arguments.

disjoin returns an object of the same type as x containing disjoint ranges for each distinct (seqname, strand) pairing. The names (names(x)) and the metadata columns in x are dropped.

isDisjoint returns a logical value indicating whether the ranges in x are disjoint (i.e. non-overlapping).

disjointBins returns bin indexes for the ranges in x, such that ranges in the same bin do not overlap. If ignore.strand=FALSE, the two features cannot overlap if they are on different strands. On a GRangesList object When they are supported on GRangesList object x, the above inter range transformations will apply the transformation to each of the list elements in x and return a list-like object parallel to x (i.e. with 1 list element per list element in x). If x has names on it, they're propagated to the returned object.

See Also

• The GenomicRanges and GRanges classes.

• The Ranges class in the IRanges package.

• The inter-range-methods man page in the IRanges package.

• GenomicRanges-comparison for comparing and ordering genomic ranges.

• endoapply in the S4Vectors package.

Examples

gr <- GRanges(
        seqnames=Rle(paste("chr", c(1, 2, 1, 3), sep=""), c(1, 3, 2, 4)),
        ranges=IRanges(1:10, width=10:1, names=letters[1:10]),
        strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)),
        score=1:10,
        GC=seq(1, 0, length=10)
      )
gr

gr1 <- GRanges(seqnames="chr2", ranges=IRanges(3, 6),
               strand="+", score=5L, GC=0.45)
gr2 <- GRanges(seqnames="chr1",
               ranges=IRanges(c(10, 7, 19), width=5),
               strand=c("+", "-", "+"), score=3:5, GC=c(0.3, 0.5, 0.66))
gr3 <- GRanges(seqnames=c("chr1", "chr2"),
               ranges=IRanges(c(1, 4), c(3, 9)),
               strand=c("-", "-"), score=c(6L, 2L), GC=c(0.4, 0.1))
grl <- GRangesList(gr1=gr1, gr2=gr2, gr3=gr3)
grl

## ---------------------------------------------------------------------
## range()
## ---------------------------------------------------------------------

## On a GRanges object:
range(gr)

## On a GRangesList object:
range(grl)
range(grl, ignore.strand=TRUE)

# ---------------------------------------------------------------------
## reduce()
## ---------------------------------------------------------------------
reduce(gr)

gr2 <- reduce(gr, with.revmap=TRUE)
revmap <- mcols(gr2)$revmap  # an IntegerList

## Use the mapping from reduced to original ranges to group the original
## ranges by reduced range:
relist(gr[unlist(revmap)], revmap)

## Or use it to split the DataFrame of original metadata columns by
## reduced range:
relist(mcols(gr)[unlist(revmap), ], revmap)  # a SplitDataFrameList

## [For advanced users] Use this reverse mapping to compare the reduced
## ranges with the ranges they originate from:
expanded_gr2 <- rep(gr2, elementNROWS(revmap))
reordered_gr <- gr[unlist(revmap)]
codes <- pcompare(expanded_gr2, reordered_gr)
## All the codes should translate to "d", "e", "g", or "h" (the 4 letters
## indicating that the range on the left contains the range on the right):
alphacodes <- rangeComparisonCodeToLetter(pcompare(expanded_gr2, reordered_gr))
stopifnot(all(alphacodes %in% c("d", "e", "g", "h")))

## On a big GRanges object with a lot of seqlevels:
mcols(gr) <- NULL
biggr <- c(gr, GRanges("chr1", IRanges(c(4, 1), c(5, 2)), strand="+"))
seqlevels(biggr) <- paste0("chr", 1:2000)
biggr <- rep(biggr, 25000)
set.seed(33)
seqnames(biggr) <- sample(factor(seqlevels(biggr), levels=seqlevels(biggr)),
                          length(biggr), replace=TRUE)

biggr2 <- reduce(biggr, with.revmap=TRUE)
revmap <- mcols(biggr2)$revmap
expanded_biggr2 <- rep(biggr2, elementNROWS(revmap))
reordered_biggr <- biggr[unlist(revmap)]
codes <- pcompare(expanded_biggr2, reordered_biggr)
alphacodes <- rangeComparisonCodeToLetter(pcompare(expanded_biggr2,
                                                  reordered_biggr))
stopifnot(all(alphacodes %in% c("d", "e", "g", "h")))
table(alphacodes)

## On a GRangesList object:
reduce(grl)  # Doesn't really reduce anything but note the reordering
             # of the inner elements in the 2nd and 3rd list elements:
             # the ranges are reordered by sequence name first (which
             # should appear in the same order as in 'seqlevels(grl)'),
             # and then by strand.
reduce(grl, ignore.strand=TRUE)  # 2nd list element got reduced

## ---------------------------------------------------------------------
## gaps()
## ---------------------------------------------------------------------
gaps(gr, start=1, end=10)

## ---------------------------------------------------------------------
## disjoin(), isDisjoint(), disjointBins()
## ---------------------------------------------------------------------
disjoin(gr)
isDisjoint(gr)
stopifnot(isDisjoint(disjoin(gr)))
disjointBins(gr)
stopifnot(all(sapply(split(gr, disjointBins(gr)), isDisjoint)))

Run the code above in your browser using DataCamp Workspace