extractReads {mosaics} | R Documentation

## Load read-level data and extract reads corresponding to each peak region

### Description

Load read-level data and extract reads corresponding to each peak region in the `MosaicsPeak` class object, which is a peak calling result.

### Usage

    extractReads( object, ... )
    ## S4 method for signature 'MosaicsPeak'
    extractReads( object, chipFile=NULL, chipFileFormat=NULL,
        chipPET=FALSE, chipFragLen=200,
        controlFile=NULL, controlFileFormat=NULL,
        controlPET=FALSE, controlFragLen=200, keepReads=FALSE,
        parallel=FALSE, nCore=8, tempDir=NULL, perl="perl" )

### Arguments

`object` | Object of class `MosaicsPeak`, a peak list object obtained using either functions `mosaicsPeak` or `mosaicsPeakHMM`.
`chipFile` | Name of the aligned read file for ChIP sample.
`chipFileFormat` | Format of the aligned read file for ChIP sample. Currently, `constructBins` permits the following aligned read file formats for SET data (`chipPET = FALSE`): `"eland_result"` (Eland result), `"eland_extended"` (Eland extended), `"eland_export"` (Eland export), `"bowtie"` (default Bowtie), `"sam"` (SAM), `"bam"` (BAM), `"bed"` (BED), and `"csem"` (CSEM). For PET data (`chipPET = TRUE`), the following aligned read file formats are allowed: `"eland_result"` (Eland result), `"sam"` (SAM), and `"bam"` (BAM).
`chipPET` | Is the file of ChIP sample paired-end tag (PET) data? If `chipPET=FALSE`, it is assumed that the file is SET data. If `chipPET=TRUE`, it is assumed that the file is PET data. Default is `FALSE` (SET data).
`chipFragLen` | Average fragment length of ChIP sample. Default is 200. This argument is ignored if `chipPET=TRUE`.
`controlFile` | Name of the aligned read file for matched control sample.
`controlFileFormat` | Format of the aligned read file for matched control sample. Currently, `constructBins` permits the following aligned read file formats for SET data (`controlPET = FALSE`): `"eland_result"` (Eland result), `"eland_extended"` (Eland extended), `"eland_export"` (Eland export), `"bowtie"` (default Bowtie), `"sam"` (SAM), `"bam"` (BAM), `"bed"` (BED), and `"csem"` (CSEM). For PET data (`controlPET = TRUE`), the following aligned read file formats are allowed: `"eland_result"` (Eland result), `"sam"` (SAM), and `"bam"` (BAM).
`controlPET` | Is the file of matched control sample paired-end tag (PET) data? If `controlPET=FALSE`, it is assumed that the file is SET data. If `controlPET=TRUE`, it is assumed that the file is PET data. Default is `FALSE` (SET data).
`controlFragLen` | Average fragment length of matched control sample. Default is 200. This argument is ignored if `controlPET=TRUE`.
`keepReads` | Keep read-level data? Default is `FALSE` (do not keep read-level data).
`parallel` | Utilize multiple CPUs for parallel computing using `"parallel"` package? Possible values are `TRUE` (utilize multiple CPUs) or `FALSE` (do not utilize multiple CPUs). Default is `FALSE` (do not utilize multiple CPUs).
`nCore` | Number of CPUs when parallel computing is utilized.
`tempDir` | Directory to store temporary files. If `tempDir=NULL`, `extractReads()` will use the temporary directory used by R.
`perl` | Name of the perl executable to be called. Default is `"perl"`.
`...` | Other parameters to be passed through to generic `extractReads`.

### Details

Read-level data is first loaded from aligned read files, and then the reads corresponding to each peak region are extracted and incorporated into the `MosaicsPeak` class object. `extractReads` currently supports the following aligned read file formats for SET data (`chipPET = FALSE` and `controlPET = FALSE`): Eland result (`"eland_result"`), Eland extended (`"eland_extended"`), Eland export (`"eland_export"`), default Bowtie (`"bowtie"`), SAM (`"sam"`), BAM (`"bam"`), BED (`"bed"`), and CSEM (`"csem"`). For PET data (`chipPET = FALSE` and `controlPET = FALSE`), the following aligned read file formats are allowed: `"eland_result"` (Eland result), `"sam"` (SAM), and `"bam"` (BAM).

If input file format is neither BED nor CSEM BED, this method retains only reads mapping uniquely to the reference genome.

### Value

Construct `MosaicsPeak` class object.

### Author(s)

Dongjun Chung, Pei Fen Kuan, Rene Welch, Sunduz Keles

### References

Kuan, PF, D Chung, G Pan, JA Thomson, R Stewart, and S Keles (2011), "A Statistical Framework for the Analysis of ChIP-Seq Data", Journal of the American Statistical Association, Vol. 106, pp. 891-903.

Chung, D, Zhang Q, and Keles S (2014), "MOSAiCS-HMM: A model-based approach for detecting regions of histone modifications from ChIP-seq data", Datta S and Nettleton D (eds.), Statistical Analysis of Next Generation Sequencing Data, Springer.

### See Also

`mosaicsPeak`, `mosaicsPeakHMM`, `export`, `findSummit`, `adjustBoundary`, `filterPeak`, `MosaicsPeak`.

### Examples

    ## Not run:
    library(mosaicsExample)

    constructBins( infile=system.file( file.path("extdata","wgEncodeBroadHistoneGm12878H3k4me3StdAlnRep1_chr22_sorted.bam"), package="mosaicsExample"),
        fileFormat="bam", outfileLoc="./",
        byChr=FALSE, useChrfile=FALSE, chrfile=NULL, excludeChr=NULL,
        PET=FALSE, fragLen=200, binSize=200, capping=0 )
    constructBins( infile=system.file( file.path("extdata","wgEncodeBroadHistoneGm12878ControlStdAlnRep1_chr22_sorted.bam"), package="mosaicsExample"),
        fileFormat="bam", outfileLoc="./",
        byChr=FALSE, useChrfile=FALSE, chrfile=NULL, excludeChr=NULL,
        PET=FALSE, fragLen=200, binSize=200, capping=0 )

    binHM <- readBins( type=c("chip","input"),
        fileName=c( "./wgEncodeBroadHistoneGm12878H3k4me3StdAlnRep1_chr22_sorted.bam_fragL200_bin200.txt",
        "./wgEncodeBroadHistoneGm12878ControlStdAlnRep1_chr22_sorted.bam_fragL200_bin200.txt" ) )
    fitHM <- mosaicsFit( binHM, analysisType="IO", bgEst="rMOM" )
    hmmHM <- mosaicsFitHMM( fitHM, signalModel = "2S",
      init="mosaics", init.FDR = 0.05, parallel=TRUE, nCore=8 )
    peakHM <- mosaicsPeakHMM( hmmHM, FDR = 0.05, decoding="posterior",
      thres=10, parallel=TRUE, nCore=8 )

    peakHM <- extractReads( peakHM,
      chipFile=system.file( file.path("extdata","wgEncodeBroadHistoneGm12878H3k4me3StdAlnRep1_chr22_sorted.bam"), package="mosaicsExample"),
      chipFileFormat="bam", chipPET=FALSE, chipFragLen=200,
      controlFile=system.file( file.path("extdata","wgEncodeBroadHistoneGm12878ControlStdAlnRep1_chr22_sorted.bam"), package="mosaicsExample"),
      controlFileFormat="bam", controlPET=FALSE, controlFragLen=200, parallel=TRUE, nCore=8 )
    peakHM <- findSummit( peakHM, parallel=TRUE, nCore=8 )
    peakHM <- adjustBoundary( peakHM, parallel=TRUE, nCore=8 )
    peakHM <- filterPeak( peakHM, parallel=TRUE, nCore=8 )

    ## End(Not run)

[Package mosaics version 2.18.0 Index]