R/AllClasses.R

Defines functions ExoData

Documented in ExoData

##' @importFrom biovizBase flatGrl
##' @importFrom Rsamtools ScanBamParam scanBamFlag
##' @importFrom GenomicAlignments readGAlignments 
##' @importFrom GenomicRanges GRanges
##' @importFrom IRanges slice
##' @importFrom data.table ":=" rbindlist .N data.table as.data.table
##' @importFrom BiocParallel SnowParam bpmapply MulticoreParam
##' @import  methods
##' @import  GenomeInfoDb
##' @import utils
NULL



##' @rdname ExoData
##' @export
setClass("ExoData",
         contains = "GRanges",
         representation = representation(
             cover = "RleList",
             reads = "GRanges",
             paramDist = "list"
         ),
         prototype = prototype(
             cover = RleList(),
             reads = GRanges(),
             paramDist = list()
         ))

setValidity("ExoData",
            function(object){
                all(names(mcols(object)) == c("fwdReads","revReads",
                                              "fwdPos","revPos",
                                              "depth","uniquePos",
                                              "ARC","URC","FSR","M","A"))
            }
        )

##' ExoData object and constructors
##'
##' \code{ExoData} is a subclass of \code{GenomicRanges}, used to asses the 
##' quality of ChIP-exo/nexus sample.
##'
##' @param file a character value with location of the bam file with the aligned
##' reads.
##' @param reads a \code{GAlignments} object with the aligned reads of a ChIP-exo
##' sample. It is meant to be used instead of \code{file}.
##' @param height a numeric value indicating the value used to slice the coverage
##' of the experiment into a set of regions.
##' @param mc.cores a numeric value with the number of cores to use,
##' i.e. at most how many child processes will be run simultaneously.
##' @param nregions a numeric value indicating the number of regions sampled to 
##' estimate the quality parameter distributions. The default value is 1e3.
##' @param ntimes a numeric value indicating the number of times that regions are 
##' sampled to estimate the quality parameter distributions. The default value
##' is 1e2.
##' @param save.reads a logical value to indicate if the reads are stored in the
##' \code{ExoData} object. The default value is \code{FALSE}.
##' @param verbose a logical value indicating if the user want to receive progress
##' details. The default value is FALSE.
##' @return It returns an \code{ExoData} object with the regions obtained after
##' partitioning the genome and the summary statistics for each region. If the
##' \code{save.reads} parameter is \code{TRUE} then it contains a \code{GRanges}
##' object with the reads of the ChIP-exo experiment.
##' @aliases ExoData ExoData-class
##'
##' @docType class
##'
##' @examples
##' 
##' files <- list.files(system.file("extdata",package = "ChIPexoQualExample"),
##'     full.names = TRUE)
##' ExoData(files[5],mc.cores = 2L)
##' 
##'
##' @rdname ExoData
##' @export
ExoData <- function(file = NULL, reads = NULL , height = 1 ,
                   mc.cores = getOption("mc.cores",2L),
                   save.reads = FALSE,nregions = 1e3,ntimes = 1e2,
                   verbose = TRUE)
{
    
    if(!is.null(file) & !is.null(reads)){
        stop("Both 'file' and 'reads' are available, can't use both.")
    }
    if(is.null(file) & is.null(reads)){
        stop("Both 'file' and 'reads' are NULL")
    }

    if(!is.null(file))stopifnot(is.character( file),file.exists(file))
    
    if(!is.null(reads))stopifnot(class(reads) %in% c("GAlignments","GRanges"))
    
    stopifnot(is.numeric(height),height >= 1)
    stopifnot(is.logical(save.reads))
    
    if(verbose){
        if(is.null(file))message("Using 'reads' argument")
        else message("Using 'file' argument")
    }
    if(!is.null(file)){
        if(verbose) message("Creating ExoData object using aligned reads in ",file)
    }
    if(verbose) message("Keeping reads in object: ",ifelse(save.reads,"Yes","No"))
    
    if(!is.null(file)){
        if(verbose) message("Loading experiment reads")
        paramFwd <- ScanBamParam(flag = scanBamFlag(isMinusStrand = FALSE))
        paramRev <- ScanBamParam(flag = scanBamFlag(isMinusStrand = TRUE))    
        
        fwdReads <- readGAlignments(file,param = paramFwd)
        revReads <- readGAlignments(file,param = paramRev)
    }else{
        fwdReads <- subset(reads,as.character(strand(reads)) == "+")
        revReads <- subset(reads,as.character(strand(reads)) == "-")
        file <- ""
    }
    
    if(class(fwdReads) == "GAlignments")fwdReads <- as(fwdReads,"GRanges")
    if(class(revReads) == "GAlignments")revReads <- as(revReads,"GRanges")
    
    cover <- coverage(fwdReads) + coverage(revReads)
    
    rlist <- slice(cover,lower = height,rangesOnly = TRUE)
    
    if(any(vapply(rlist,length,0L) ==  0)){
        chr <- names(which(vapply(rlist,length,0L) > 0))
        rlist <- rlist[chr]
    }else{
        chr <- names(rlist)
    }
    
    fwdReads <- split(fwdReads,as.character(seqnames(fwdReads)))
    revReads <- split(revReads,as.character(seqnames(revReads)))
    
    fwdReads <- fwdReads[chr]
    revReads <- revReads[chr]
    
    if(verbose) message("Calculating summary statistics")
    
    if(Sys.info()[["sysname"]] == "Windows"){
        snow <- SnowParam(workers = mc.cores, type = "SOCK")
        stats <- bpmapply(calculateSummary,rlist,fwdReads,revReads,
                         BPPARAM = snow,SIMPLIFY = FALSE)       
    }else{
        stats <- bpmapply(calculateSummary,rlist,fwdReads,revReads,
            BPPARAM = MulticoreParam(workers = mc.cores),
            SIMPLIFY = FALSE)       
    }

    regions <- as(rlist,"GRanges")
    mcols(regions) <- do.call(rbind,stats)
    nreads <- sum(vapply(fwdReads,length,1)) + sum(vapply(revReads, length, 1))
    
    if(save.reads){
        fwdReads <- biovizBase::flatGrl(fwdReads)
        mcols(fwdReads) <- NULL
        revReads <- biovizBase::flatGrl(revReads)
        mcols(revReads) <- NULL
        reads <- c(fwdReads,revReads)
    }else{
        reads <- GRanges()
    }
    depth <- uniquePos <- width <-  NULL
    
    if(verbose) message("Calculating quality scores distribution")

    DT <- formatRegions(regions)

    paramList <- lapply(seq_len(ntimes),calculateParamDist,DT,nregions)
                          
    param <- rbindlist(paramList)

    estimate <- term <- NULL
    
    rm(paramList,DT)
    paramDist <- list("beta1" = param[term == "uniquePos",(estimate)] ,
                      "beta2" = param[term == "width",(estimate)])
    
    metadata(regions) <- list("file"=file,"nreads"=nreads,
                             "ntimes"=ntimes,"nregions"=nregions)
    if(verbose) message("Done!")
    new("ExoData",regions,cover = cover,
        reads = reads,
        paramDist = paramDist)
}

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ChIPexoQual documentation built on Nov. 8, 2020, 8:22 p.m.