R/tagMatrix.R

Defines functions getTagMatrix2.binning.internal getTagMatrix2.internal getTagMatrix2 getTagMatrix.binning.internal getTagMatrix.internal getTagMatrix makeBioRegionFromGranges getBioRegion getPromoters

Documented in getBioRegion getPromoters getTagMatrix getTagMatrix2 getTagMatrix2.binning.internal getTagMatrix2.internal getTagMatrix.binning.internal getTagMatrix.internal makeBioRegionFromGranges

##' prepare the promoter regions
##'
##'
##' @title getPromoters
##' @param TxDb TxDb
##' @param upstream upstream from TSS site
##' @param downstream downstream from TSS site
##' @param by one of gene or transcript
##' @return GRanges object
##' @export
getPromoters <- function(TxDb=NULL,
                         upstream=1000,
                         downstream=1000,
                         by = "gene") {
  
  getBioRegion(TxDb = TxDb,
               upstream = upstream,
               downstream = downstream,
               by = by,
               type = "start_site")
}


##' prepare a bioregion of selected feature
##' 
##' this function combined previous functions getPromoters(), getBioRegion() and getGeneBody() in order
##' to solve the following issues.
##' 
##' (1) \url{https://github.com/GuangchuangYu/ChIPseeker/issues/16}
##' 
##' (2) \url{https://github.com/GuangchuangYu/ChIPseeker/issues/87}
##' 
##' The getBioRegion() function can prevoid a region of interest from
##' \code{txdb} object. There are three kinds of regions, \code{start_site},
##' \code{end_site} and \code{body}. 
##' 
##' We take transcript region to expain the differences of these three regions.
##' tx: chr1 1000 1400. 
##' 
##' \code{body} region refers to the 1000-1400bp.
##' 
##' \code{start_site} region with \code{upstream = 100, downstream = 100} refers to 900-1100bp. 
##' 
##' \code{end_site} region with \code{upstream = 100, downstream = 100} refers to 1300-1500bp.
##'
##' @title getBioRegion
##' @param TxDb TxDb
##' @param upstream upstream from start site or end site
##' @param downstream downstream from start site or end site
##' @param by one of 'gene', 'transcript', 'exon', 'intron' , '3UTR' , '5UTR', 'UTR'
##' @param type one of "start_site", "end_site", "body"
##' @return GRanges object
##' @import BiocGenerics IRanges GenomicRanges
##' @author Guangchuang Yu, Ming L
##' @export
getBioRegion <- function(TxDb=NULL,
                         upstream=1000,
                         downstream=1000,
                         by="gene",
                         type="start_site"){
  
  by <- match.arg(by, c('gene', 'transcript', 'exon', 'intron' , '3UTR' , '5UTR','UTR'))
  type <- match.arg(type, c("start_site", "end_site", "body"))
  
  TxDb <- loadTxDb(TxDb)
  .ChIPseekerEnv(TxDb)
  ChIPseekerEnv <- get("ChIPseekerEnv", envir=.GlobalEnv)
  
  label <- make_label(type = type, by = by)
  
  
  if(by == 'gene' || by == 'transcript'){
    regions <- getGene(TxDb, by)
  }
  
  if (by == "exon") {
    exonList <- get_exonList(ChIPseekerEnv)
    regions <-  unlist(exonList)
  }
  
  if (by == "intron") {
    intronList <- get_intronList(ChIPseekerEnv)
    regions <- unlist(intronList)
  }
  
  if (by == "3UTR") {
    threeUTRList <- threeUTRsByTranscript(TxDb)
    regions <- unlist(threeUTRList)
  }
  
  if (by == "5UTR") {
    fiveUTRList <- fiveUTRsByTranscript(TxDb)
    regions <- unlist(fiveUTRList)
  }
  
  if (by == 'UTR'){
    three_URT <- threeUTRsByTranscript(TxDb)
    three_UTR_regions <- unlist(three_URT)
    five_UTR <- fiveUTRsByTranscript(TxDb)
    five_UTR_regions <- unlist(five_UTR)
    regions <- c(three_UTR_regions,five_UTR_regions)
  }
  
  if(type == "start_site"){
    coordinate<- ifelse(strand(regions) == "+", start(regions), end(regions))
  }else if(type == "end_site"){
    coordinate<- ifelse(strand(regions) == "+", end(regions), start(regions))
  }else{
    ## assign attribute 
    attr(regions, 'type') = type
    attr(regions, 'by') = by
    attr(regions, 'label') = label
    
    return(regions)
  }
  
  ## issue and code obtained from Chen Ting(NIH/NCI)
  start_site <- ifelse(strand(regions) == "+",coordinate-upstream, coordinate-downstream)
  end_site <- ifelse(strand(regions) == "+", coordinate+downstream, coordinate+upstream)
  
  bioRegion <- GRanges(seqnames=seqnames(regions),
                       ranges=IRanges(start_site, end_site),
                       strand=strand(regions))
  bioRegion <- unique(bioRegion)
  
  ## assign attribute 
  attr(bioRegion, 'type') = type
  attr(bioRegion, 'by') = by
  
  ## different region have different label to be added to the figures
  ## so we attach label to the Granges object
  attr(bioRegion, 'label') = label
  
  attr(bioRegion, 'upstream') = upstream
  attr(bioRegion, 'downstream') = downstream
  
  return(bioRegion)
}

##' make windows from granges object
##' 
##' \code{makeBioRegionFromGranges()} function can make bioregion from granges object.
##' 
##' The differences between \code{makeBioRegionFromGranges()} and \code{getBioRegion()} is that
##' \code{getBioRegion()} get the region object from \code{txdb} object but
##' \code{makeBioRegionFromGranges()} get the region from the granges object provided by users.
##' For example, \code{txdb} object do not contain insulator or enhancer regions. Users can
##' provide these regions through self-made granges object
##' 
##' There are three kinds of regions, \code{start_site}, \code{end_site} and \code{body}. 
##' 
##' We take enhancer region to explain the differences of these three regions.
##' enhancer: chr1 1000 1400. 
##' 
##' \code{body} region refers to the 1000-1400bp.
##' 
##' \code{start_site} region with \code{upstream = 100, downstream = 100} refers to 900-1100bp. 
##' 
##' \code{end_site} region with \code{upstream = 100, downstream = 100} refers to 1300-1500bp.
##'
##' In \code{makeBioRegionFromGranges()}, \code{upstream} and \code{downstream} can be
##' \code{NULL} if the \code{type == 'body'}. \code{by} should be specified by users and 
##' can not be omitted. \code{by} parameter will be used to made labels. \code{type} should also
##' be specified.
##' 
##' \url{https://github.com/YuLab-SMU/ChIPseeker/issues/189}
##' 
##' @title makeBioRegionFromGranges
##' 
##' @param gr a grange object contain region of interest
##' @param upstream upstream from start site or end site, can be NULL if the type == 'body'
##' @param downstream downstream from start site or end site, can be NULL if the type == 'body'
##' @param by specify be users, e.g. gene, insulator, enhancer
##' @param type one of "start_site", "end_site", "body"
##' @return GRanges object
##' @import BiocGenerics IRanges GenomicRanges
##' @export
makeBioRegionFromGranges <- function(gr,
                                     by,
                                     type,
                                     upstream=1000,
                                     downstream=1000){
  
  if (!is(gr, "GRanges")) {
    stop("windows should be a GRanges object...")
  }
  
  type <- match.arg(type, c("start_site", "end_site", "body"))
  
  label <- make_label(type = type, by = by)
  regions <- gr
  
  if(type == "start_site"){
    coordinate<- ifelse(strand(regions) == "+", start(regions), end(regions))
  }else if(type == "end_site"){
    coordinate<- ifelse(strand(regions) == "+", end(regions), start(regions))
  }else{
    ## assign attribute 
    attr(regions, 'type') = type
    attr(regions, 'by') = by
    attr(regions, 'label') = label
    
    return(regions)
  }
  
  ## issue and code obtained from Chen Ting(NIH/NCI)
  start_site <- ifelse(strand(regions) == "+",coordinate-upstream, coordinate-downstream)
  end_site <- ifelse(strand(regions) == "+", coordinate+downstream, coordinate+upstream)
  
  bioRegion <- GRanges(seqnames=seqnames(regions),
                       ranges=IRanges(start_site, end_site),
                       strand=strand(regions))
  bioRegion <- unique(bioRegion)
  
  ## assign attribute 
  attr(bioRegion, 'type') = type
  attr(bioRegion, 'by') = by
  attr(bioRegion, 'label') = label
  attr(bioRegion, 'upstream') = upstream
  attr(bioRegion, 'downstream') = downstream
  
  return(bioRegion)
  
}


##' calculate the tag matrix
##' 
##' \code{getTagMatrix()} function can produce the matrix for visualization.
##' \code{peak} stands for the peak file. 
##' \code{window} stands for a collection of regions that users want to look into. 
##' Users can use \code{window} to capture the peak of interest.
##' There are two ways to input \code{window}. 
##' 
##' The first way is that users can use
##' \code{getPromoters()/getBioRegion()/makeBioRegionFromGranges()} to 
##' get \code{window} and put it into \code{getTagMatrix()}. 
##' 
##' The second way is that users can use \code{getTagMatrix()} to
##' call \code{getPromoters()/getBioRegion()/makeBioRegionFromGranges()}. In this way
##' users do not need to input \code{window} parameter but they need to input
##' \code{txdb}. 
##' 
##' \code{txdb} is a set of packages contained annotation 
##' of regions of different genomes. Users can
##' get the regions of interest through specific functions. These specific functions
##' are built in \code{getPromoters()/getBioRegion()}. Many regions can not be gain
##' through \code{txdb}, like insulator and enhancer regions. 
##' Users can provide these regions in the form of granges object. 
##' These self-made granges object will be passed to \code{TxDb} parameter and they will
##' be passed to \code{makeBioRegionFromGranges()} to produce the \code{window}.
##' In a word, \code{TxDb} parameter is a reference information. Users can
##' pass \code{txdb object} or self-made granges into it.
##' 
##' Details see \code{\link{getPromoters}},\code{\link{getBioRegion}} and \code{\link{makeBioRegionFromGranges}}
##' 
##' \code{upstream} and \code{downstream} parameter have different usages:
##' 
##' (1) \code{window} parameter is provided, 
##' 
##' if \code{type == 'body'}, \code{upstream} and \code{downstream} can use to extend 
##' the flank of body region.
##' 
##' if \code{type == 'start_site'/'end_site'}, \code{upstream} and \code{downstream} do not
##' play a role in \code{getTagMatrix()} function.
##' 
##' (2) \code{window} parameter is missing,
##' 
##' if \code{type == 'body'}, \code{upstream} and \code{downstream} can use to extend 
##' the flank of body region.
##' 
##' if \code{type == 'start_site'/'end_site'}, \code{upstream} and \code{downstream} refer to
##' the upstream and downstream of the start_site or the end_site.
##' 
##' \code{weightCol} refers to column in peak file. This column acts as a weight vaule. Details
##' see \url{https://github.com/YuLab-SMU/ChIPseeker/issues/15}
##' 
##' \code{nbin} refers to the number of bins. \code{getTagMatrix()} provide a binning method
##' to get the tag matrix.
##' 
##' @title getTagMatrix
##'
##' @param peak peak peak file or GRanges object
##' @param upstream the distance of upstream extension
##' @param downstream the distance of downstream extension
##' @param windows a collection of region
##' @param type one of "start_site", "end_site", "body"
##' @param by one of 'gene', 'transcript', 'exon', 'intron', '3UTR' , '5UTR', or specified by users
##' @param TxDb TxDb or self-made granges object, served as txdb
##' @param weightCol column name of weight, default is NULL
##' @param nbin the amount of nbines 
##' @param verbose print message or not
##' @param ignore_strand ignore the strand information or not
##' @return tagMatrix
##' @importFrom ggplot2 rel
##' @export
getTagMatrix <- function(peak, 
                         upstream,
                         downstream, 
                         windows,
                         type,
                         by,
                         TxDb=NULL,
                         weightCol = NULL, 
                         nbin = NULL,
                         verbose = TRUE,
                         ignore_strand= FALSE){
  
  is_GRanges_of_TxDb <- FALSE
  if (is(TxDb, "GRanges")) {
    is_GRanges_of_TxDb <- TRUE
    message("#\n#.. 'TxDb' is a self-defined 'GRanges' object...\n#")
  }
  
  if(missingArg(windows)){
    
    if(is_GRanges_of_TxDb){
      
      ## make windows from self-made granges object
      windows <- makeBioRegionFromGranges(gr=TxDb,
                                          by=by,
                                          type=type,
                                          upstream=upstream,
                                          downstream=downstream)
      
    }else{
      
      ## make windows from txdb object
      windows <- getBioRegion(TxDb=TxDb,
                              upstream=upstream,
                              downstream=downstream,
                              by=by,
                              type=type)
      
      
    }
    
  }else{
    
    if (!is(windows, "GRanges")) {
      stop("windows should be a GRanges object...")
    }
    
    if(is.null(attr(windows,'type'))){
      stop("windows should be made from getPromoters()/getBioRegion()/makeBioRegionFromGranges()")
    }
    
    type <- attr(windows, 'type')
    by <- attr(windows, 'by')
    
  }
  
  # check the upstream and downstream parameter
  if(type == "body"){
    if(missingArg(upstream)){
      upstream <- NULL
    }
    
    if(missingArg(downstream)){
      downstream <- NULL
    }
    
  }else{
    upstream <- attr(windows, 'upstream')
    downstream <- attr(windows, 'downstream')
  }
  
  ## check upstream and downstream parameter
  check_upstream_and_downstream(upstream = upstream, downstream = downstream)
  
  if(type != 'body'){
    if(inherits(upstream, 'rel') || is.null(upstream)){
      stop("upstream and downstream for site region should be actual number...")
    }
  }
  
  ## check nbin parameters
  if(!is.null(nbin) && !is.numeric(nbin)){
    stop('nbin should be NULL or numeric...')
  }
  
  if(type == 'body' && is.null(nbin)){
    stop('plotting body region should set the nbin parameter...')
  }
  
  ## check nbin parameter
  if(!is.null(nbin)){
    cat(">> binning method is used...",
        format(Sys.time(), "%Y-%m-%d %X"), "\n",sep = "")
    
    is.binning <- TRUE
  }else{
    
    is.binning <- FALSE
  }
  
  if (verbose) {
    cat(">> preparing ",type," regions"," by ",by,"... ",
        format(Sys.time(), "%Y-%m-%d %X"), "\n",sep = "")
  }
  
  
  if(is.binning){
    
    if (verbose) {
      cat(">> preparing tag matrix by binning... ",
          format(Sys.time(), "%Y-%m-%d %X"), "\n")
    }
    
    tagMatrix <- getTagMatrix.binning.internal(peak = peak, 
                                               weightCol = weightCol, 
                                               windows = windows, 
                                               nbin = nbin,
                                               upstream = upstream,
                                               downstream = downstream,
                                               ignore_strand = ignore_strand)
  }else{
    
    if (verbose) {
      cat(">> preparing tag matrix... ",
          format(Sys.time(), "%Y-%m-%d %X"), "\n")
    }
    
    tagMatrix <- getTagMatrix.internal(peak=peak, 
                                       weightCol=weightCol, 
                                       windows=windows, 
                                       ignore_strand=ignore_strand)
  }
  
  ## assign attribute 
  attr(tagMatrix, 'upstream') = upstream
  attr(tagMatrix, 'downstream') = downstream
  attr(tagMatrix, 'type') = attr(windows, 'type')
  attr(tagMatrix, 'label') = attr(windows, 'label')
  attr(tagMatrix, "is.binning") <- is.binning
  
  return(tagMatrix)
}


##' calculate the tag matrix
##'
##'
##' @title getTagMatrix.internal
##' @param peak peak file or GRanges object
##' @param weightCol column name of weight, default is NULL
##' @param windows a collection of region with equal size, eg. promoter region.
##' @param ignore_strand ignore the strand information or not
##' @return tagMatrix
##' @import BiocGenerics S4Vectors IRanges GenomeInfoDb GenomicRanges
##' @author G Yu
getTagMatrix.internal <- function(peak, 
                                  weightCol=NULL, 
                                  windows, 
                                  ignore_strand= FALSE) {
  peak.gr <- loadPeak(peak)
  
  if (! is(windows, "GRanges")) {
    stop("windows should be a GRanges object...")
  }
  if (length(unique(width(windows))) != 1) {
    stop("width of windows should be equal...")
  }
  
  ## if (!exists("ChIPseekerEnv", envir = .GlobalEnv)) {
  ##     assign("ChIPseekerEnv", new.env(), .GlobalEnv)
  ## }
  ## ChIPseekerEnv <- get("ChIPseekerEnv", envir = .GlobalEnv)
  
  ## if (exists("peak", envir=ChIPseekerEnv, inherits=FALSE) &&
  ##     exists("promoters", envir=ChIPseekerEnv, inherits=FALSE) &&
  ##     exists("weightCol", envir=ChIPseekerEnv, inherits=FALSE) &&
  ##     exists("tagMatrix", envir=ChIPseekerEnv, inherits=FALSE) ) {
  
  ##     pp <- get("peak", envir=ChIPseekerEnv)
  ##     promoters <- get("promoters", envir=ChIPseekerEnv)
  ##     w <- get("weightCol", envir=ChIPseekerEnv)
  
  ##     if (all(pp == peak)) {
  ##         if (all(windows == promoters)) {
  ##             if ( (is.null(w) && is.null(weightCol)) ||
  ##                 (!is.null(w) && !is.null(weightCol) && w == weightCol)) {
  ##                 tagMatrix <- get("tagMatrix", envir=ChIPseekerEnv)
  ##                 return(tagMatrix)
  ##             } else {
  ##                 assign("weightCol", weightCol, envir=ChIPseekerEnv)
  ##             }
  ##         } else {
  ##             assign("promoters", windows)
  ##             ## make sure it is not conflict with getPromoters
  ##             if ( exists("upstream", envir=ChIPseekerEnv, inherits=FALSE))
  ##                 rm("upstream", envir=ChIPseekerEnv)
  ##         }
  ##     } else {
  ##         assign("peak", peak, envir=ChIPseekerEnv)
  ##     }
  
  ## }
  
  ## if ( !exists("peak", envir=ChIPseekerEnv, inherits=FALSE)) {
  ##     assign("peak", peak, envir=ChIPseekerEnv)
  ## }
  
  ## if ( !exists("promoters", envir=ChIPseekerEnv, inherits=FALSE)) {
  ##     assign("promoters", windows, envir=ChIPseekerEnv)
  ## }
  
  ## if (!exists("weightCol", envir=ChIPseekerEnv, inherits=FALSE)) {
  ##     assign("weightCol", weightCol, envir=ChIPseekerEnv)
  ## }
  if (is.null(weightCol)) {
    peak.cov <- coverage(peak.gr)
  } else {
    weight <- mcols(peak.gr)[[weightCol]]
    peak.cov <- coverage(peak.gr, weight=weight)
  }
  cov.len <- elementNROWS(peak.cov)
  cov.width <- GRanges(seqnames=names(cov.len),
                       IRanges(start=rep(1, length(cov.len)),
                               end=cov.len))
  windows <- subsetByOverlaps(windows, cov.width,
                              type="within", ignore.strand=FALSE)
  
  chr.idx <- intersect(names(peak.cov),
                       unique(as.character(seqnames(windows))))
  
  peakView <- Views(peak.cov[chr.idx], as(windows, "IntegerRangesList")[chr.idx])
  tagMatrixList <- lapply(peakView, function(x) t(viewApply(x, as.vector)))
  tagMatrix <- do.call("rbind", tagMatrixList)
  
  ## get the index of windows, that are reorganized by as(windows, "IntegerRangesList")
  idx.list <- split(1:length(windows),  as.factor(seqnames(windows)))
  idx <- do.call("c", idx.list)
  
  rownames(tagMatrix) <- idx
  tagMatrix <- tagMatrix[order(idx),]
  
  ## minus strand
  if (!ignore_strand) {
    minus.idx <- which(as.character(strand(windows)) == "-")
    tagMatrix[minus.idx,] <- tagMatrix[minus.idx, ncol(tagMatrix):1]
  }
  
  tagMatrix <- tagMatrix[rowSums(tagMatrix)!=0,]
  ## assign("tagMatrix", tagMatrix, envir=ChIPseekerEnv)
  return(tagMatrix)
}


##' calculate the tagMatrix by binning
##' the idea was derived from the function of deeptools
##' https://deeptools.readthedocs.io/en/develop/content/tools/computeMatrix.html 
##' 
##' @title getTagMatrix.binning.internal
##' @param peak peak peak file or GRanges object
##' @param weightCol weightCol column name of weight, default is NULL
##' @param windows windows a collection of region with equal or not equal size, eg. promoter region, gene region.
##' @param nbin the amount of nbines needed to be splited and it should not be more than min_body_length
##' @param upstream rel object, NULL or actual number
##' @param downstream rel object, NULL or actual number
##' @param ignore_strand ignore the strand information or not
##' @import BiocGenerics S4Vectors IRanges GenomeInfoDb GenomicRanges 
##' @importFrom ggplot2 rel
##' @return tagMatrix 
getTagMatrix.binning.internal <- function(peak, 
                                          weightCol = NULL, 
                                          windows, 
                                          nbin = 800,
                                          upstream = NULL,
                                          downstream = NULL,
                                          ignore_strand = FALSE){
  
  min_body_length <- filter_length <- nbin
  peak.gr <- loadPeak(peak)
  type <- attr(windows, 'type')
  
  
  if (!is(windows, "GRanges")) {
    stop("windows should be a GRanges object...")
  }
  
  if (is.null(weightCol)) {
    peak.cov <- coverage(peak.gr)
  } else {
    weight <- mcols(peak.gr)[[weightCol]]
    peak.cov <- coverage(peak.gr, weight=weight)
  }
  
  
  cov.len <- elementNROWS(peak.cov)
  cov.width <- GRanges(seqnames=names(cov.len),
                       IRanges(start=rep(1, length(cov.len)),
                               end=cov.len))
  
  windows <- subsetByOverlaps(windows, 
                              cov.width,
                              type="within", 
                              ignore.strand=FALSE)
  
  ## extend the windows by rel object
  if(inherits(upstream, 'rel')){
    
    windows1 <- windows
    
    if(!ignore_strand){
      
      positive_index <- which(as.character(strand(windows1)) == "+")
      negative_index <- which(as.character(strand(windows1)) == "-")
      start(windows1)[positive_index] <- suppressWarnings(start(windows1)[positive_index] - floor(width(windows)[positive_index]*as.numeric(upstream)))
      end(windows1)[positive_index] <- suppressWarnings(end(windows1)[positive_index] + floor(width(windows)[positive_index]*as.numeric(downstream)))
      
      start(windows1)[negative_index] <- suppressWarnings(start(windows1)[negative_index] - floor(width(windows)[negative_index]*as.numeric(downstream)))
      end(windows1)[negative_index] <- suppressWarnings(end(windows1)[negative_index] + floor(width(windows)[negative_index]*as.numeric(upstream)))
      
    }else{
      
      start(windows1) <- suppressWarnings(start(windows1) - floor(width(windows)*as.numeric(upstream)))
      end(windows1) <- suppressWarnings(end(windows1) + floor(width(windows)*as.numeric(downstream)))
      
    }
   
    windows <- windows1
    nbin <- floor(nbin*(1+as.numeric(downstream)+as.numeric(upstream)))
    min_body_length <- min_body_length*(1+as.numeric(upstream)+as.numeric(downstream))
    
    cat(">> preparing matrix with extension from (",attr(windows,'label')[1],"-",
        100*as.numeric(upstream),"%)~(",attr(windows,'label')[2],"+",
        100*as.numeric(downstream),"%)... ",
        format(Sys.time(), "%Y-%m-%d %X"),"\n",sep = "")
  }
  
  ## do not extend
  if(is.null(upstream)){
    if(attr(windows, 'type') == 'body'){
      cat(">> preparing matrix for ",attr(windows, 'type')," region with no flank extension... ",
          format(Sys.time(), "%Y-%m-%d %X"),"\n",sep = "")
    }else{
      cat(">> preparing matrix for ",attr(windows,'type')," region... ",
          format(Sys.time(), "%Y-%m-%d %X"),"\n",sep = "")
    }
  }
  
  ## extend the windows by actual number 
  if(!is.null(upstream) && !inherits(upstream, 'rel') && attr(windows, 'type')== 'body'){
    
    windows1 <- windows
    
    if(!ignore_strand){
      
      positive_index <- which(as.character(strand(windows1)) == "+")
      negative_index <- which(as.character(strand(windows1)) == "-")
      
      start(windows1)[positive_index] <- suppressWarnings(start(windows1)[positive_index] - upstream)
      end(windows1)[positive_index] <- suppressWarnings(end(windows1)[positive_index] + downstream)
      
      start(windows1)[negative_index] <- suppressWarnings(start(windows1)[negative_index] - downstream)
      end(windows1)[negative_index] <- suppressWarnings(end(windows1)[negative_index] + upstream)
      
    }else{
      
      start(windows1) <- suppressWarnings(start(windows1) - upstream)
      end(windows1) <- suppressWarnings(end(windows1) + downstream)
      
    }
    
    windows <- windows1
    upstreamPer <- floor(upstream/1000)*0.1
    downstreamPer <- floor(downstream/1000)*0.1
    nbin <- floor(nbin*(1+upstreamPer+downstreamPer))
    min_body_length <- min_body_length+upstream+downstream
    
    cat(">> preparing matrix with flank extension from (",attr(windows,'label')[1],"-",
        upstream,"bp)~(",attr(windows,'label')[2],"+",downstream,"bp)... ",
        format(Sys.time(), "%Y-%m-%d %X"),"\n",sep = "")
  }
  
  chr.idx <- intersect(names(peak.cov),
                       unique(as.character(seqnames(windows))))
  
  windows <- as(windows, "IntegerRangesList")[chr.idx]
  attr(windows,'type') <- type
  
  peakView <- Views(peak.cov[chr.idx], 
                    windows)
  
  ## remove the gene that has no binding proteins
  for (i in 1:length(peakView)) {
    
    index <- viewSums(peakView[[i]])!= 0
    peakView[[i]] <- peakView[[i]][index]
    windows[[i]] <- windows[[i]][index]
  } 
  
  tagMatrixList <- lapply(peakView, function(x) viewApply(x, as.vector))
  
  if(!attr(windows, 'type') == 'body'){
    
    tagMatrixList <- lapply(tagMatrixList, function(x) t(x))
    
    # to remove the chromosome that do not bind protein
    index <- vapply(tagMatrixList, function(x) length(x)>0, FUN.VALUE = logical(1))
    tagMatrixList <- tagMatrixList[index]
    windows <- windows[index]
    
    ## create a matrix to receive binning results
    tagMatrix <- list()
    
    ## this circulation is to deal with different chromosomes
    for (i in 1:length(tagMatrixList)) {
      
      tagMatrix[[i]] <- matrix(nrow = nrow(tagMatrixList[[i]]),ncol = nbin)
      
      ## this circulation is to deal with different genes
      for (j in 1:nrow(tagMatrixList[[i]])) {
        
        ## seq is the distance between different bins
        seq <- floor(length(tagMatrixList[[i]][j,])/nbin)
        
        ## cursor record the position of calculation
        cursor <- 1
        
        ## the third circulation is to calculate the binding strength
        ## it has two parts
        ## the first part is to for the nbin(1:nbin-1)
        ## because the seq is not derived from exact division
        ## the second part is to compensate the loss of non-exact-division
        
        ## this the first part for 1:(nbin-1)
        for (k in 1:(nbin-1)) {
          
          read <- 0
          
          for (z in cursor:(cursor+seq-1)) {
            read <- read + tagMatrixList[[i]][j,z]
          }
          
          tagMatrix[[i]][j,k] <- read/seq
          
          cursor <- cursor+seq
        }
        
        ## this the second part to to compensate the loss of non-exact-division
        read <- 0
        for (z in cursor:length(tagMatrixList[[i]][j,])) {
          read <- read+tagMatrixList[[i]][j,z]
        }
        
        tagMatrix[[i]][j,nbin] <- read/(length(tagMatrixList[[i]][j,])-cursor+1)
      }
      
      if(!ignore_strand){
        minus.idx <- which(as.character(mcols(windows[[i]])[["strand"]]) == "-")
        tagMatrix[[i]][minus.idx,] <- tagMatrix[[i]][minus.idx, ncol(tagMatrix[[i]]):1]
      }
    }
    
  }else{
    
    ## extend genebody by atual number
    if(!is.null(upstream) & !inherits(upstream, 'rel')){
      
      for (i in 1:length(tagMatrixList)) {
        if (length(class(tagMatrixList[[i]])) != 1) {
          sample <- tagMatrixList[[i]]
          tagMatrixList[[i]] <- lapply(seq_len(ncol(sample)), function(i) sample[,i])  
        }
      }
      
      index <- vapply(tagMatrixList, function(x) length(x)>0, FUN.VALUE = logical(1))
      tagMatrixList <- tagMatrixList[index]
      windows <- windows[index]
      
      ## count the amount before filtering
      pre_amount <- 0
      for(i in 1:length(tagMatrixList)){
        pre_amount <- pre_amount+length(tagMatrixList[[i]])
      }
      
      for (i in 1:length(tagMatrixList)) {
        
        index <- vapply(tagMatrixList[[i]], function(y) length(y)>min_body_length,FUN.VALUE = logical(1))
        tagMatrixList[[i]] <- tagMatrixList[[i]][index]
        windows[[i]] <- windows[[i]][index]
      }
      
      ## count the amount after filtering
      amount <- 0
      for(i in 1:length(tagMatrixList)){
        amount <- amount+length(tagMatrixList[[i]])
      }
      
      cat(">> ",pre_amount-amount," peaks(",100*((pre_amount-amount)/pre_amount),
          "%), having lengths smaller than ",filter_length,"bp, are filtered... ",
          format(Sys.time(), "%Y-%m-%d %X"),"\n",sep = "")
      
      upstreamnbin <- floor(nbin*(upstreamPer/(1+upstreamPer+downstreamPer)))
      bodynbin <- floor(nbin*(1/(1+upstreamPer+downstreamPer)))
      downstreamnbin <- floor(nbin*(downstreamPer/(1+upstreamPer+downstreamPer)))
      
      tagMatrix <- list()
      
      for (i in 1:length(tagMatrixList)) {
        
        tagMatrix[[i]] <- matrix(nrow = length(tagMatrixList[[i]]),ncol = nbin)
        
        ## count the upstream 
        for (j in 1:length(tagMatrixList[[i]])) {
          
          seq <- floor(upstream/upstreamnbin)
          cursor <- 1
          
          for (k in 1:(upstreamnbin-1)) {
            
            read <- 0
            
            for (z in cursor:(cursor+seq-1)) {
              read <- read + tagMatrixList[[i]][[j]][z]
            }
            
            tagMatrix[[i]][j,k] <- read/seq
            
            cursor <- cursor+seq
          }
          
          
          read <- 0
          for (z in cursor:upstream) {
            read <- read+tagMatrixList[[i]][[j]][z]
          }
          
          tagMatrix[[i]][j,upstreamnbin] <- read/(upstream-cursor)
          
        }
        
        ## count genebody
        for (j in 1:length(tagMatrixList[[i]])) {
          
          seq <- floor((length(tagMatrixList[[i]][[j]])-upstream-downstream)/bodynbin)
          cursor <- upstream+1
          
          for (k in (upstreamnbin+1):(upstreamnbin+bodynbin-1)) {
            
            read <- 0
            
            for (z in cursor:(cursor+seq-1)) {
              read <- read + tagMatrixList[[i]][[j]][z]
            }
            
            tagMatrix[[i]][j,k] <- read/seq
            
            cursor <- cursor+seq
          }
          
          read <- 0
          for (z in cursor:(length(tagMatrixList[[i]][[j]])-downstream)) {
            read <- read+tagMatrixList[[i]][[j]][z]
          }
          
          tagMatrix[[i]][j,bodynbin+upstreamnbin] <- read/(length(tagMatrixList[[i]][[j]])-downstream-cursor)
        }
        
        ## count downstream
        for (j in 1:length(tagMatrixList[[i]])) {
          
          seq <- floor(downstream/downstreamnbin)
          cursor <- length(tagMatrixList[[i]][[j]])-downstream+1
          
          for (k in (upstreamnbin+bodynbin+1):(nbin-1)) {
            
            read <- 0
            
            for (z in cursor:(cursor+seq-1)) {
              read <- read + tagMatrixList[[i]][[j]][z]
            }
            
            tagMatrix[[i]][j,k] <- read/seq
            
            cursor <- cursor+seq
          }
          
          read <- 0
          for (z in cursor:length(tagMatrixList[[i]][[j]])) {
            read <- read+tagMatrixList[[i]][[j]][z]
          }
          
          tagMatrix[[i]][j,nbin] <- read/(length(tagMatrixList[[i]][[j]])-cursor+1)
        }
        
        if(!ignore_strand){
          minus.idx <- which(as.character(mcols(windows[[i]])[["strand"]]) == "-")
          tagMatrix[[i]][minus.idx,] <- tagMatrix[[i]][minus.idx, ncol(tagMatrix[[i]]):1]
        }
        
      }
      
    }else{
      
      for (i in 1:length(tagMatrixList)) {
        if (length(class(tagMatrixList[[i]])) != 1) {
          sample <- tagMatrixList[[i]]
          tagMatrixList[[i]] <- lapply(seq_len(ncol(sample)), function(i) sample[,i])  
        }
      }
      
      index <- vapply(tagMatrixList, function(x) length(x)>0, FUN.VALUE = logical(1))
      tagMatrixList <- tagMatrixList[index]
      windows <- windows[index]
      
      ## count the amount before filtering
      pre_amount <- 0
      for(i in 1:length(tagMatrixList)){
        pre_amount <- pre_amount+length(tagMatrixList[[i]])
      }
      
      for (i in 1:length(tagMatrixList)) {
        
        index <- vapply(tagMatrixList[[i]], function(y) length(y)>min_body_length,FUN.VALUE = logical(1))
        tagMatrixList[[i]] <- tagMatrixList[[i]][index]
        windows[[i]] <- windows[[i]][index]
      }
      
      ## count the amount after filtering
      amount <- 0
      for(i in 1:length(tagMatrixList)){
        amount <- amount+length(tagMatrixList[[i]])
      }
      
      cat(">> ",pre_amount-amount," peaks(",100*((pre_amount-amount)/pre_amount),
          "%), having lengths smaller than ",filter_length,"bp, are filtered... ",
          format(Sys.time(), "%Y-%m-%d %X"),"\n",sep = "")
  
      tagMatrix <- list()
      
      for (i in 1:length(tagMatrixList)) {
        
        tagMatrix[[i]] <- matrix(nrow = length(tagMatrixList[[i]]),ncol = nbin)
        
        for (j in 1:length(tagMatrixList[[i]])) {
          
          seq <- floor(length(tagMatrixList[[i]][[j]])/nbin)
          cursor <- 1
          
          for (k in 1:(nbin-1)) {
            
            read <- 0
            
            for (z in cursor:(cursor+seq-1)) {
              read <- read + tagMatrixList[[i]][[j]][z]
            }
            
            tagMatrix[[i]][j,k] <- read/seq
            
            cursor <- cursor+seq
          }
          
          read <- 0
          for (z in cursor:length(tagMatrixList[[i]][[j]])) {
            read <- read+tagMatrixList[[i]][[j]][z]
          }
          
          tagMatrix[[i]][j,nbin] <- read/(length(tagMatrixList[[i]][[j]])-cursor+1)
          
        }
        
        if(!ignore_strand){
          minus.idx <- which(as.character(mcols(windows[[i]])[["strand"]]) == "-")
          tagMatrix[[i]][minus.idx,] <- tagMatrix[[i]][minus.idx, ncol(tagMatrix[[i]]):1]
        }
      }
      
    }
    
  }
  
  ## combine the results
  tagMatrix <- do.call("rbind",tagMatrix)
  
  return(tagMatrix)
}


##' Nested function for getTagMatrix() to deal with multiple windows
##' 
##' This is an internal function.
##' @title getTagMatrix2
##'
##' @param peak peak peak file or GRanges object
##' @param upstream the distance of upstream extension
##' @param downstream the distance of downstream extension
##' @param windows_name the names of windows
##' @param type one of "start_site", "end_site", "body"
##' @param by one of 'gene', 'transcript', 'exon', 'intron', '3UTR' , '5UTR', or specified by users
##' @param TxDb TxDb or self-made granges object, served as txdb
##' @param weightCol column name of weight, default is NULL
##' @param nbin the amount of nbines 
##' @param verbose print message or not
##' @param ignore_strand ignore the strand information or not
##' @return tagMatrix
##' @importFrom ggplot2 rel
getTagMatrix2 <- function(peak, 
                          upstream,
                          downstream,
                          windows_name,
                          type,
                          by,
                          TxDb=NULL,
                          weightCol = NULL, 
                          nbin = NULL,
                          verbose = TRUE,
                          ignore_strand= FALSE){
  
  names(TxDb) <- by
  
  windows <- lapply(as.list(by), function(x){
    
    if(x %in% c('gene', 'transcript', 'exon', 'intron' , '3UTR' , '5UTR', 'UTR')){
      
      result <- getBioRegion(TxDb=TxDb[[x]],
                             upstream=upstream,
                             downstream=downstream,
                             by=x,
                             type=type)
    }else{
      
      result <- makeBioRegionFromGranges(gr=TxDb[[x]],
                                         by=x,
                                         type=type,
                                         upstream=upstream,
                                         downstream=downstream)
      
    }
    
    return(result)
    
  })
  
  names(windows) <- windows_name
  
  # check the upstream and downstream parameter for body
  if(type == "body"){
    if(missingArg(upstream)){
      upstream <- NULL
    }
    
    if(missingArg(downstream)){
      downstream <- NULL
    }
    
  }else{
    upstream <- attr(windows[[1]], 'upstream')
    downstream <- attr(windows[[1]], 'downstream')
  }
  
  ## check upstream and downstream parameter
  check_upstream_and_downstream(upstream = upstream, downstream = downstream)
  
  if(type != 'body'){
    if(inherits(upstream, 'rel') || is.null(upstream)){
      stop("upstream and downstream for site region should be actual number...")
    }
  }
  
  ## check nbin parameters
  if(!is.null(nbin) && !is.numeric(nbin)){
    stop('nbin should be NULL or numeric...')
  }
  
  if(type == 'body' && is.null(nbin)){
    stop('plotting body region should set the nbin parameter...')
  }
  
  ## check nbin parameter
  if(!is.null(nbin)){
    cat(">> binning method is used...",
        format(Sys.time(), "%Y-%m-%d %X"), "\n",sep = "")
    
    is.binning <- TRUE
  }else{
    
    is.binning <- FALSE
  }
  
  if (verbose) {
    cat(">> preparing ",type," regions"," by ",paste(by,collapse = " "),"... ",
        format(Sys.time(), "%Y-%m-%d %X"), "\n",sep = "")
  }
  
  
  if(is.binning){
    
    if (verbose) {
      cat(">> preparing tag matrix by binning... ",
          format(Sys.time(), "%Y-%m-%d %X"), "\n")
    }
    
    tagMatrix <- getTagMatrix2.binning.internal(peak = peak, 
                                                weightCol = weightCol, 
                                                windows = windows, 
                                                windows_name=windows_name,
                                                nbin = nbin,
                                                upstream = upstream,
                                                downstream = downstream,
                                                ignore_strand = ignore_strand)
  }else{
    
    if (verbose) {
      cat(">> preparing tag matrix... ",
          format(Sys.time(), "%Y-%m-%d %X"), "\n")
    }
    
    tagMatrix <- getTagMatrix2.internal(peak=peak, 
                                        weightCol=weightCol,
                                        windows=windows,
                                        windows_name=windows_name,
                                        ignore_strand=ignore_strand)
  }
  
  names(tagMatrix) <- windows_name
  
  ## assign attribute 
  tagMatrix <- lapply(tagMatrix, function(x){
    attr(x, 'upstream') = upstream
    attr(x, 'downstream') = downstream
    attr(x, 'type') = attr(windows[[1]], 'type')
    attr(x, 'label') = attr(windows[[1]], 'label')
    attr(x, "is.binning") <- is.binning
    return(x)
  })
  
  return(tagMatrix)
  
}

##' @title getTagMatrix2.internal
##'
##' @param peak peak peak file or GRanges object
##' @param windows a collection of region
##' @param windows_name the name of windows
##' @param weightCol column name of weight, default is NULL
##' @param ignore_strand ignore the strand information or not
getTagMatrix2.internal <- function(peak, 
                                   weightCol=NULL,
                                   windows,
                                   windows_name,
                                   ignore_strand= FALSE) {
  
  mt_list <- lapply(windows_name, function(x){
    
    windows_tmp <- windows[[x]]
    
    mt <- getTagMatrix.internal(peak=peak, 
                                weightCol=weightCol, 
                                windows=windows_tmp, 
                                ignore_strand=ignore_strand)
    
    return(mt)
  })
  
  return(mt_list)
}

##' internal function
##' 
##' @param peak peak peak file or GRanges object
##' @param upstream the distance of upstream extension
##' @param downstream the distance of downstream extension
##' @param windows a collection of region
##' @param windows_name the name of windows
##' @param weightCol column name of weight, default is NULL
##' @param nbin the amount of nbines 
##' @param ignore_strand ignore the strand information or not
getTagMatrix2.binning.internal <- function(peak, 
                                           weightCol = NULL, 
                                           windows, 
                                           windows_name,
                                           nbin = 800,
                                           upstream = NULL,
                                           downstream = NULL,
                                           ignore_strand = FALSE){
  
  mt_list <- lapply(windows_name, function(x){
    
    windows_tmp <- windows[[x]]
    
    mt <- getTagMatrix.binning.internal(peak = peak, 
                                        weightCol = weightCol, 
                                        windows = windows_tmp, 
                                        nbin = nbin,
                                        upstream = upstream,
                                        downstream = downstream,
                                        ignore_strand = ignore_strand)
    
    return(mt)
  })
  
  return(mt_list)
  
}
YuLab-SMU/ChIPseeker documentation built on Nov. 2, 2024, 1:45 p.m.