Inter range transformations of a RangedSummarizedExperiment object

Description

This man page documents the inter range transformations that are supported on RangedSummarizedExperiment objects.

Usage

## S4 method for signature 'RangedSummarizedExperiment'
isDisjoint(x, ignore.strand=FALSE)

## S4 method for signature 'RangedSummarizedExperiment'
disjointBins(x, ignore.strand=FALSE)

Arguments

Details

These transformations operate on the rowRanges component of the RangedSummarizedExperiment object, which can be a GenomicRanges or GRangesList object.

More precisely, any of the above functions performs the following transformation on RangedSummarizedExperiment object x:

    f(rowRanges(x), ...)

where f is the name of the function and ... any additional arguments passed to it.

See ?isDisjoint in the GenomicRanges package for the details of how these transformations operate on a GenomicRanges or GRangesList object.

Value

See ?isDisjoint in the GenomicRanges package.

See Also

• RangedSummarizedExperiment objects.

• The isDisjoint man page in the GenomicRanges package where inter range transformations of a GenomicRanges or GRangesList object are documented.

Examples

nrows <- 20; ncols <- 6
counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)
rowRanges <- GRanges(rep(c("chr1", "chr2"), c(5, 15)),
                     IRanges(sample(1000L, 20), width=100),
                     strand=Rle(c("+", "-"), c(12, 8)))
colData <- DataFrame(Treatment=rep(c("ChIP", "Input"), 3),
                     row.names=LETTERS[1:6])
rse0 <- SummarizedExperiment(assays=SimpleList(counts=counts),
                             rowRanges=rowRanges, colData=colData)
rse1 <- shift(rse0, 99*start(rse0))

isDisjoint(rse0)  # FALSE
isDisjoint(rse1)  # TRUE

bins0 <- disjointBins(rse0)
bins0
stopifnot(identical(bins0, disjointBins(rowRanges(rse0))))

bins1 <- disjointBins(rse1)
bins1
stopifnot(all(bins1 == bins1[1]))

Results

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> library(SummarizedExperiment)
Loading required package: GenomicRanges
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/SummarizedExperiment/inter-range-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: inter-range-methods
> ### Title: Inter range transformations of a RangedSummarizedExperiment
> ###   object
> ### Aliases: inter-range-methods isDisjoint
> ###   isDisjoint,RangedSummarizedExperiment-method disjointBins
> ###   disjointBins,RangedSummarizedExperiment-method
> ### Keywords: methods utilities
> 
> ### ** Examples
> 
> nrows <- 20; ncols <- 6
> counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)
> rowRanges <- GRanges(rep(c("chr1", "chr2"), c(5, 15)),
+                      IRanges(sample(1000L, 20), width=100),
+                      strand=Rle(c("+", "-"), c(12, 8)))
> colData <- DataFrame(Treatment=rep(c("ChIP", "Input"), 3),
+                      row.names=LETTERS[1:6])
> rse0 <- SummarizedExperiment(assays=SimpleList(counts=counts),
+                              rowRanges=rowRanges, colData=colData)
> rse1 <- shift(rse0, 99*start(rse0))
> 
> isDisjoint(rse0)  # FALSE
[1] FALSE
> isDisjoint(rse1)  # TRUE
[1] TRUE
> 
> bins0 <- disjointBins(rse0)
> bins0
 [1] 1 2 2 1 1 2 2 1 2 1 1 1 1 1 2 1 1 2 1 3
> stopifnot(identical(bins0, disjointBins(rowRanges(rse0))))
> 
> bins1 <- disjointBins(rse1)
> bins1
 [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
> stopifnot(all(bins1 == bins1[1]))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>