Annotate bin pairs

Description

Annotate bin pairs based on features overlapping the anchor regions.

Usage

annotatePairs(data.list, regions, rnames=names(regions), indices, ...) 

Arguments

Details

Entries in regions are identified with any overlap to anchor regions for interactions in data.list. The names for these entries are concatenated into a comma-separated string for easy reporting. Typically, gene symbols are used in names, but other values can be supplied depending on the type of annotation. This is done separately for the first and second anchor regions so that potential interactions between features of interest can be identified.

If indices is supplied, all interactions corresponding to each unique index are considered to be part of a single cluster. Overlaps with all interactions in the cluster are subsequently concatenated into a single string. Cluster indices should range from [1, nclusters] for any given number of clusters. This means that the annotation for a cluster corresponding to a certain index can be obtained by subsetting the output vectors with that index. Otherwise, if indices is not set, all interactions are assumed to be their own cluster, i.e., annotation is returned for each interaction separately.

Multiple InteractionSet objects can be supplied in data.list, e.g., if the cluster consists of bin pairs of different sizes. This means that indices should also be a list of vectors where each vector indicates the cluster identity of the entries in the corresponding InteractionSet of data.list.

Value

A list of two character vectors anchor1 and anchor2 is returned, containing comma-separated strings of names for entries in regions overlapped by the first and second anchor regions respectively. If indices is not specified, overlaps are identified to anchor regions of each interaction in data.list. Otherwise, overlaps are identified to anchor regions for any interaction in each cluster.

Author(s)

Aaron Lun

See Also

findOverlaps, clusterPairs

Examples

# Setting up the objects.
a <- 10
b <- 20
cuts <- GRanges(rep(c("chrA", "chrB"), c(a, b)), IRanges(c(1:a, 1:b), c(1:a, 1:b)))
param <- pairParam(cuts)

all.combos <- combn(length(cuts), 2) 
y <- InteractionSet(matrix(0, ncol(all.combos), 1), 
    GInteractions(anchor1=all.combos[2,], anchor2=all.combos[1,], regions=cuts, mode="reverse"),
    colData=DataFrame(lib.size=1000), metadata=List(param=param, width=1))

regions <- GRanges(rep(c("chrA", "chrB"), c(3,2)), IRanges(c(1,5,8,3,3), c(1,5,8,3,4)))
names(regions) <- LETTERS[seq_along(regions)] 
out <- annotatePairs(y, regions=regions)

# Again, with indices:
indices <- sample(20, length(y), replace=TRUE)
out <- annotatePairs(y, regions=regions, indices=indices)

# Again, with multiple InteractionSet objects:
out <- annotatePairs(list(y, y[1:10,]), regions=regions, indices=list(indices, indices[1:10]))

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(diffHic)
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: InteractionSet
Loading required package: SummarizedExperiment
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/diffHic/annotatePairs.Rd_%03d_medium.png", width=480, height=480)
> ### Name: annotatePairs
> ### Title: Annotate bin pairs
> ### Aliases: annotatePairs
> ### Keywords: annotation
> 
> ### ** Examples
> 
> # Setting up the objects.
> a <- 10
> b <- 20
> cuts <- GRanges(rep(c("chrA", "chrB"), c(a, b)), IRanges(c(1:a, 1:b), c(1:a, 1:b)))
> param <- pairParam(cuts)
> 
> all.combos <- combn(length(cuts), 2) 
> y <- InteractionSet(matrix(0, ncol(all.combos), 1), 
+     GInteractions(anchor1=all.combos[2,], anchor2=all.combos[1,], regions=cuts, mode="reverse"),
+     colData=DataFrame(lib.size=1000), metadata=List(param=param, width=1))
> 
> regions <- GRanges(rep(c("chrA", "chrB"), c(3,2)), IRanges(c(1,5,8,3,3), c(1,5,8,3,4)))
> names(regions) <- LETTERS[seq_along(regions)] 
> out <- annotatePairs(y, regions=regions)
> 
> # Again, with indices:
> indices <- sample(20, length(y), replace=TRUE)
> out <- annotatePairs(y, regions=regions, indices=indices)
> 
> # Again, with multiple InteractionSet objects:
> out <- annotatePairs(list(y, y[1:10,]), regions=regions, indices=list(indices, indices[1:10]))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>