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Last data update: 2014.03.03

R: Find ChIP-enriched regions on smoothed ExpressionSet

findChersOnSmoothed

R Documentation

Find ChIP-enriched regions on smoothed ExpressionSet

Description

Given an ExpressionSet of smoothed probe intensities, an environment with the mapping of probes to chromosomes, and a vector of thresholds for calling genomic sites enriched, this function finds the 'chers' (ChIP-enriched regions) consisting of enriched genomic positions, with probes mapped to them. 'Adjacent' enriched positions are condensed into a single Cher.

Usage

findChersOnSmoothed(smoothedX, probeAnno, thresholds, allChr = NULL,
   distCutOff = 600, minProbesInRow = 3, cellType = NULL,
   antibodyColumn=NULL, checkUnique = TRUE, uniqueCodes = c(0),
   verbose = TRUE)

Arguments

`smoothedX`	Object of class `ExpressionSet` holding the smoothed probe intensities, e.g. the result of function `computeRunningMedians`.
`probeAnno`	environment containing the probe to genome mapping
`thresholds`	numeric vector of threshold above which smoothed probe intensities are considered to correspond to enriched probes. The vector has to be of length equal the number of samples in `smoothedX`, with a single threshold for each sample.
`allChr`	character vector of all chromosomes on which enriched regions are sought. Every chromosome here has to have probes mapped to it in the `probeAnno` environment. By default (`NULL`) the `chromosomeNames` of the probeAnno object are used.
`distCutOff`	integer; maximum amount of base pairs at which enriched probes are condensed into one Cher.
`minProbesInRow`	integer; minimum number of enriched probes required for a Cher; see `details` for further explanation.
`cellType`	character; name of cell type the data comes from, is either a. of length one indicating the column of `pData(smoothedX)` that holds the cell type OR b. of length one indicating the common cell type for all samples in the `ExpressionSet` OR c. of length equal to `ncol(smoothedX)` specifying the cell type of each sample individually.
`antibodyColumn`	the name or number of the column of the `pData(smoothedX)` that holds the description of the antibody used for each sample. This information is used to annotate found ChIP-enriched regions accordingly. If `NULL` (default), the `sampleNames` of `smoothedX` are used.
`checkUnique`	logical; indicates whether the uniqueness indicator of probe matches from the probeAnno environment should be used.
`uniqueCodes`	numeric; which numeric codes in the chromosome-wise match-uniqueness elements of the probeAnno environment indicate uniqueness?
`verbose`	logical; extended output to STDOUT?

Details

Specifying a minimum number of probes for a Cher (argument minProbesInRow) guarantees that a Cher is supported by a reasonable number of measurements in probe-sparse regions. For example, if there's only one enriched probe within a certain genomic 1kb region and no other probes can been mapped to that region, this single probe does arguably not provide enough evidence for calling this genomic region enriched.

Value

A list of class cherList, holding objects of class cher that were found on the supplied data.

Author(s)

Joern Toedling

Examples

  exDir <- system.file("exData",package="Ringo")
  load(file.path(exDir,"exampleProbeAnno.rda"))
  load(file.path(exDir,"exampleX.rda"))
  smoothX <- computeRunningMedians(exampleX, probeAnno=exProbeAnno,
       modColumn = "Cy5", allChr = "9", winHalfSize = 400)
  chersX <- findChersOnSmoothed(smoothX, probeAnno=exProbeAnno,
       thresholds=0.45, allChr="9", distCutOff=600, cellType="human")
  if (interactive())
    plot(chersX[[1]], smoothX, probeAnno=exProbeAnno, gff=exGFF)
  chersX <- relateChers(chersX, exGFF)
  as.data.frame.cherList(chersX)

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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
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(Ringo)
Loading required package: Biobase
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

Welcome to Bioconductor

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

Loading required package: RColorBrewer
Loading required package: limma

Attaching package: 'limma'

The following object is masked from 'package:BiocGenerics':

    plotMA

Loading required package: Matrix
Loading required package: grid
Loading required package: lattice
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/Ringo/findChersOnSmoothed.Rd_%03d_medium.png", width=480, height=480)
> ### Name: findChersOnSmoothed
> ### Title: Find ChIP-enriched regions on smoothed ExpressionSet
> ### Aliases: findChersOnSmoothed
> ### Keywords: manip
> 
> ### ** Examples
> 
>   exDir <- system.file("exData",package="Ringo")
>   load(file.path(exDir,"exampleProbeAnno.rda"))
>   load(file.path(exDir,"exampleX.rda"))
>   smoothX <- computeRunningMedians(exampleX, probeAnno=exProbeAnno,
+        modColumn = "Cy5", allChr = "9", winHalfSize = 400)

Chromosome 9 ...
Suz12_vs_total ... 
Construction result ExpressionSet...Done.
>   chersX <- findChersOnSmoothed(smoothX, probeAnno=exProbeAnno,
+        thresholds=0.45, allChr="9", distCutOff=600, cellType="human")


Sample:  Suz12_vs_total.sm ...

Chr: 9 ...> #  if (interactive())
>     plot(chersX[[1]], smoothX, probeAnno=exProbeAnno, gff=exGFF)
>   chersX <- relateChers(chersX, exGFF)
Relating 2 ChIP-enriched regions to GFF:
>   as.data.frame.cherList(chersX)
                                name chr    start      end cellType
1 human.Suz12_vs_total.sm.chr9.cher1   9 34318954 34319928    human
2 human.Suz12_vs_total.sm.chr9.cher2   9 34579010 34582430    human
           antibody
1 Suz12_vs_total.sm
2 Suz12_vs_total.sm
                                                                         features
1 ENST00000379158 ENST00000379154 ENST00000379155 ENST00000346365 ENST00000337747
2                                                 ENST00000378980 ENST00000351266
  maxLevel     score
1 1.995891  69.47276
2 1.534150 104.44638
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>