R/BaalChIP-class.R

In InesdeSantiago/BaalChIP: BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes

##################################################
## BaalChIP.R - Allele specific analysis of     ##
## ChIP-seq data from cancer cell lines         ##
## 23 April 2015                                ##
## Ines de Santiago, Wei Liu,                   ##
## Ke Yuan, Florian Markowetz                   ##
## ines.desantiago@cruk.cam.ac.uk               ##
## Cancer Research UK - University of Cambridge ##
##################################################


#' BaalChIP-class
#' @author Ines de Santiago, Wei Liu, Ke Yuan, Florian Markowetz
#' @name BaalChIP
#' @param samplesheet A character string indicating the filename for a \code{.tsv} file. Column names in the \code{.tsv} file should include:
#' \itemize{
#' \item \code{group_name}: identifier string to group samples together
#' \item \code{target}: identifier string for factor (transcription factor, protein)
#' \item \code{replicate_number}: replicate number of sample
#' \item \code{bam_name}: file path for BAM file containing aligned reads for ChIP sample. If duplicated reads are flaged they will not be included in the allelic count data
#' \item \code{bed_name}: path for BED file containing peaks for ChIP sample
#' \item \code{SampleID}: identifier string for sample. If not given will use <group_name>_<target>_<replicate_number>
#' }
#' @param hets A named vector with filenames for the \code{.txt} variant files to be used. The names in the vector should correspond to \code{group_name} strings in the \code{.tsv} samplesheet. Columns names in the \code{.txt} file should include:
#' \itemize{
#' \item ID: unique identifier string per variant. Identifiers have to be unique, and no more than one identifier should be present per data record. If there is no identifier available, then use an arbritary name to name each variant
#' \item CHROM: chromosome identifier from the reference genome per variant (same genome build as BAM and BED files provided)
#' \item POS: the reference position (1-based)
#' \item REF: reference base. Each base must be one of A,C,G,T in uppercase. Multiple bases are not permitted
#' \item ALT: alternate non-reference base. Each base must be one of A,C,G,T in uppercase. Multiple bases are not permitted
#' \item RAF: [Optional] a value ranging from 0 to 1 for each variant denoting the relative allele frequency (RAF). A value between 0.5 and 1 denotes a bias to the reference allele, and a value between 0 and 0.5 a bias to the alternate allele. If neither RAF or \code{CorrectWithgDNA} are given, BaalChIP will not correct for relative allele frequency (copy-number) bias. If both RAF and \code{CorrectWithgDNA} are given, BaalChIP will give priority to the RAF values of the 'hets' files and will use these values to correct for relative allele frequency (copy-number) bias.
#' }
#' @param CorrectWithgDNA An optional named list with comple file paths for the \code{.bam} gDNA files to be used. The names in the list should correspond to \code{group_name} strings in the \code{.tsv} samplesheet. Allelic read counts from all gDNA files are pooled together to generate the Reference Allelic Ratios (RAF) directly from input data. If missing, BaalChIP will try to read the background allelic ratios from the information in the RAF column of the 'hets' files indicated by the \code{hets} parameter. If both \code{RAF} and \code{CorrectWithgDNA} are missing, BaalChIP will not correct for relative allele frequency (copy-number) bias.
#' @description This S4 class includes a series of methods for detecting allele-specific events from multiple ChIP-seq datasets.
#' @return .Object An object of the \code{\link{BaalChIP}} class.
#' @examples
#'samplesheet <- system.file("test", "exampleChIP.tsv", package = "BaalChIP")  
#'hets <- c("MCF7"= system.file("test", "MCF7_hetSNP.txt", package = "BaalChIP"), 
#'          "GM12891"= system.file("test", "GM12891_hetSNP.txt", package = "BaalChIP"))
#'res <- new("BaalChIP", samplesheet=samplesheet, hets=hets)
#'res <- BaalChIP(samplesheet=samplesheet, hets=hets)

BaalChIP <- setClass(
    #BaalChIPexperiment class
    "BaalChIP",


    slots = c(
                samples = "data.frame",
                hets = "character",
                gDNA = "list",
                alleleCounts = "list",
                mergedCounts = "list",
                assayedVar = "list",
                VarTable = "list",
                biasTable = "list",
                ASB = "list",
                param   = "list",
                simulation_stats = "data.frame"
                ),

    prototype = c(
        samplesheet = data.frame(),
        hets = "",
        gDNA = list(),
        alleleCounts = list(),
        mergedCounts = list(),
        assayedVar = list(),
        VarTable = list(),
        biasTable = list(),
        ASB = list(),
        param = list(),
        simulation_stats = data.frame()
        )

)