Creating a Data4Cseq object

Description

This function creates a Data4Cseq object. Data on the 4C-seq experiment, e.g. the chromosome of the viewpoint, is stored and checked for consistency.

Usage

Data4Cseq(viewpointChromosome, viewpointInterval, readLength, pointsOfInterest, rawReads)

Arguments

Details

A Data4Cseq object contains basic information for the corresponding 4C-seq experiment, including the viewpoint chromosome, the viewpoint region and reads from the experiment. See Data4Cseq-class for more details. The constructor collects the basic data; fragment data or normalized read counts are added later.

Fragments at the experiment's viewpoint are usually vastly overrepresented due to self-ligation; chooseNearCisFragments offers the option to discard all fragments in the specified viewpoint region. The specified viewpoint interval of a Data4Cseq object is supposed to correspond to the positions of the biological primers on the genome, but can also be increased in size if more fragments around the viewpoint should be removed.

Value

An instance of the Data4Cseq class.

Author(s)

Carolin Walter

See Also

Data4Cseq-class

Examples

  # create a Data4Cseq object with a minimum of data
  liverData = Data4Cseq(viewpointChromosome = "10", viewpointInterval = c(20879870, 20882209), readLength = 54)
  liverData

  # create a Data4Cseq object, including possible points of interest and raw reads 
  bamFile <- system.file("extdata", "fetalLiverShort.bam", package="Basic4Cseq")
  liverReads <- readGAlignments(bamFile)
  pointsOfInterestFile <- system.file("extdata", "fetalLiverVP.bed", package="Basic4Cseq")
  liverData = Data4Cseq(viewpointChromosome = "10", viewpointInterval = c(20879870, 20882209), readLength = 54, pointsOfInterest = readPointsOfInterestFile(pointsOfInterestFile), rawReads = liverReads)
  liverData

Results

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> library(Basic4Cseq)
Loading required package: Biostrings
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: XVector
Loading required package: GenomicAlignments
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
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")'.

Loading required package: Rsamtools
Loading required package: caTools

Attaching package: 'caTools'

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

    runmean

The following object is masked from 'package:S4Vectors':

    runmean

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/Basic4Cseq/Data4Cseq.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Data4Cseq
> ### Title: Creating a Data4Cseq object
> ### Aliases: Data4Cseq
> ###   Data4Cseq,character,numeric,numeric,data.frame,GAlignments-method
> ###   Data4Cseq,character,numeric,numeric,missing,missing-method
> ### Keywords: Data4Cseq
> 
> ### ** Examples
> 
>   # create a Data4Cseq object with a minimum of data
>   liverData = Data4Cseq(viewpointChromosome = "10", viewpointInterval = c(20879870, 20882209), readLength = 54)
>   liverData
4C-seq experiment data
Type: Data4Cseq 
Viewpoint:  10 : 20879870 - 20882209 
Read length:  30 
Number of reads:  0 
Number of total fragments:  0 
Number of near-cis fragments:  0 
Points of interest:  0 
> 
>   # create a Data4Cseq object, including possible points of interest and raw reads 
>   bamFile <- system.file("extdata", "fetalLiverShort.bam", package="Basic4Cseq")
>   liverReads <- readGAlignments(bamFile)
>   pointsOfInterestFile <- system.file("extdata", "fetalLiverVP.bed", package="Basic4Cseq")
>   liverData = Data4Cseq(viewpointChromosome = "10", viewpointInterval = c(20879870, 20882209), readLength = 54, pointsOfInterest = readPointsOfInterestFile(pointsOfInterestFile), rawReads = liverReads)
>   liverData
4C-seq experiment data
Type: Data4Cseq 
Viewpoint:  10 : 20879870 - 20882209 
Read length:  54 
Number of reads:  2185 
Number of total fragments:  0 
Number of near-cis fragments:  0 
Points of interest:  2 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>