ChIPSeqSpikeDataset-class: ChIPSeqSpikeDataset Reference Class
In ChIPSeqSpike: ChIP-Seq data scaling according to spike-in control

Description Fields Constructor Arguments Getters Setters Details Author(s) See Also Examples

Main class containing file paths, scores and values for spike normalization. It inherits from ChIPSeqSpikeCore.

experimentList: A list of Experiment objects

ChIPSeqSpikeDataset(endogenousBam_vec, exogenousBam_vec, bigWigFile_endogenous_vec, inputBigWigFile, inputBamFile, expnames, inputSF = 0, inputNb = 0, SetArrayList = list(), matBindingList = list())

endogenousBam_vec: Character vector of file paths to the BAM files aligned to the reference genome.
exogenousBam_vec: Character vector of file paths to the BAM files aligned to the exogenous genome.
bigWigFile_endogenous_vec: Character vector of file paths to the bigWig files aligned to the reference genome.
inputBigWigFile: String representing the file path to the input control bigWig file. (see details)
inputBamFile: String representing the file path to the input control BAM file.
expnames: Character vector of experiment names. (see details)
inputSF: Numeric scaling factor. Default is 0. (see details)
inputNb: Numeric read counts. Default is 0. (see details)
SetArrayList: List of PlotSetArray objects. Default is an empty list. (see details)
matBindingList: List of binding value matrices. Default is an empty list. (see details)

getBam: Returns the input BAM path
getBigWigFile: Returns the input bigWig path
getExperimentListBigWigs: Returns a character vector of paths to the experiment bigWig files
getExpName: Returns a character vector of experiment names
getScalingFactor: Returns the input scaling factor
getCount: Returns the number of reads contained in the input BAM file
getAverageBindingValues: Returns a list of PlotSetArray objects. (see details)
getMatBindingValues: Returns a list of matrices containing binding values. (see details)
x[[i]]: Get the Experiment object at index i

scalingFactor: Modifies the input scaling factor value
count: Modifies the input count value
bigWigFile: Modifies the input bigWig file path
averageBindingValues: Modifies the PlotSetArray list. (see details)
matBindingValues: Modifies the list of binding value matrices. (see details)
x[[i]] <- value: Set value to ChIPSeqSpikeDataset i

'expnames' character vector is used to define the names of the experiment list and are used as labels in plotting, summary and getRatio functions.

'inputSF' is the scaling factor that will be applied to the input bigWigFile before input subtraction of the different experiments. 'inputNb' which holds the number of aligned reads is used to calculate the aforementioned factor. Only the endogenous count and factor are needed for the input conversely to the experiments for which both the endogenous/exogenous scaling factors and counts are needed to perform spike-in normalization.

'SetArrayList' contains PlotSetArray objects. The PlotSetArray class is defined in the Bioconductor package 'seqplots' and holds the values that are necessary to plot profiles and heatmaps. These values can be retrieved with the 'getAverageBindingValues' function.

'matBindingList' contains matrices of binding values for each experiment. These values are used to generate boxplots and correlations plots. They are retrieved by calling the function 'BWGFile_summary' of the bioconductor package 'rtracklayer'.

If the dataset contains more than one input, one would want to use the ChIPSeqSpikeDatasetList class. Boost mode classes (ChIPSeqSpikeDatasetBoost and ChIPSeqSpikeDatasetListBoost) can also be considered to speed up the analysis.

Nicolas Descostes

Experiment-class ChIPSeqSpikeCore-class ChIPSeqSpikeDatasetBoost-class ChIPSeqSpikeDatasetList-class spikeDataset PlotSetArray-class spikeSummary getRatio

file_vec <- system.file("extdata", 
                        c("bam_files/H3K79me2_0_dm3-filtered.bam", 
                        "bam_files/H3K79me2_0_hg19-filtered.bam", 
                        "bigwig_files/H3K79me2_0-filtered.bw", 
                        "bigwig_files/input_0-filtered.bw", 
                        "bam_files/input_0_hg19-filtered.bam"),
                        package="ChIPSeqSpike")

csds <- ChIPSeqSpikeDataset(endogenousBam_vec = file_vec[2],
                         exogenousBam_vec = file_vec[1],
                         bigWigFile_endogenous_vec = file_vec[3], 
                         inputBigWigFile = file_vec[4], 
                         inputBamFile = file_vec[5], 
                         expnames = "H3K79me2_0")
csds