R/TODO/nucleoCluster-methods.R

In nucleosome-dynamics/nucleR: Nucleosome positioning package for R

###############################################################################
# Internal function for detection plotting
###############################################################################
.doPlot <- function(res, calls, cover, window, plot.limy)
{
    chr <- as.character(res$chrom)
    pos <- res$pos
    id  <- as.character(res$id)

    # Plot peaks and calls
    plotPeaks(data  = as.numeric(cover[[chr]]),
              peaks = calls[chr],
              xlim  = pos + c(-window, window),
              main  = id,
              ylim  = c(0, plot.limy))
    abline(v=pos, col="red", lwd=2)

    # Add +1 nucleosome
    if (!is.na(res$p1.pos)) {
        text(res$p1.pos,
             plot.limy/4*3,
             paste0("+1 (", res$p1.class, ")")
             cex=1,
             font=2)
        abline(v=res$p1.pos, col="darkgreen", lty=3)
    }

    # Add -1 nucleosome
    if (!is.na(res$m1.pos)) {
        text(res$m1.pos,
             plot.limy / 4 * 3,
             paste0("-1 (", res$m1.class, ")"),
             cex=1,
             font=2)
        abline(v=res$m1.pos, col="darkorchid", lty=3)
    }

    # Add arrow for strand
    if (!is.na(res$p1.pos) & !is.na(res$m1.pos)) {
        arrows(res$m1.pos,
               plot.limy / 4 * 3.3,
               res$p1.pos,
               plot.limy / 4 * 3.3,
               lwd=1,
               length=0.10,
               col="black")
    } else {
        str <- ifelse(res$strand == "+", 1, -1)
        arrows(pos + (-25*str),
               plot.limy / 4 * 3.3,
               pos - (-25*str),
               plot.limy / 4 * 3.3,
               lwd=2,
               length=0.10,
               col="darkgrey")
    }

    # Add distance
    if (!is.na(res$p1.pos) & !is.na(res$m1.pos)) {
        text((res$m1.pos + res$p1.pos)/2,
             plot.limy / 4 * 3.35,
             paste("dist =", res$dist),
             cex=0.8,
             font=3,
             adj=c(0.5, 0))
    }

    # Add message
    if (res$msg != "") {
        text(pos,
             plot.limy / 8 * 7,
             adj=c(0.5,0),
             substr(x=res$msg, start=4, stop=nchar(res$msg)),
             font=4)
    }
}

###############################################################################
#Multiple execution using data.frame
###############################################################################
nucleosomePatternsDF <- function (calls, cover=NULL, df, col.id="name",
                                  col.chrom="chrom", col.pos="pos",
                                  col.strand="strand", show.plot=FALSE,
                                  mc.cores=1, ...)
{
    # Check if nmerge is in the column
    if (!"nmerge" %in% colnames(calls)) {
        warning("Column 'nmerge' not found in 'calls'. Running mergeCalls ",
                "with default parameters")
        calls <- mergeCalls(calls)
    }

    # Cannot plot if mc.cores>1, parallel output not supported
    if (mc.cores > 1 & show.plot) {
        stop("'show.plot=TRUE' cannot work with 'mc.cores > 1'")
    }

    # We need the coverage for plotting
    if (is.null(cover) & show.plot) {
        stop("'cover' should be provided if 'show.plot=TRUE'")
    }

    #mc.cores = .check.mc(mc.cores) #TODO: Uncomment after testing

    # Parallel execution
    if (mc.cores > 1) {
        res <- mclapply(1:nrow(df),
                        function(x)
                            nucleosomePatterns(calls  = calls,
                                               cover  = cover,
                                               id     = df[x, col.id],
                                               chrom  = df[x, col.chrom],
                                               pos    = df[x, col.pos],
                                               strand = df[x, col.strand],
                                               ...),
                        mc.cores=mc.cores)

    #Serial execution
    } else {
        res <- lapply(1:nrow(df),
                      function(x)
                          nucleosomePatterns(calls     = calls,
                                             cover     = cover,
                                             id        = df[x, col.id],
                                             chrom     = df[x, col.chrom],
                                             pos       = df[x, col.pos],
                                             strand    = df[x, col.strand],
                                             show.plot = show.plot,
                                             ...))
    }

    # Join results in a single data.frame
    res <- do.call("rbind", res)
    return(res)
}


###############################################################################
# Pattern detection in a single locus
###############################################################################
nucleosomePatterns <- function (calls, cover=NULL, id, chrom, pos, strand="+",
                                window=300, show.plot=FALSE, plot.limy=20,
                                p1.max.merge=3, p1.max.downstream=20,
                                open.thresh=215, wp.thresh.score_w=0.6,
                                wp.thresh.score_h=0.4, max.uncovered=150)
{
    # Error if asking for plot without coverage
    if (is.null(cover) & show.plot) {
        stop("'cover' should be provided if 'show.plot=TRUE'")
    }

    # Check if nmerge is in the data.frame
    if (!"nmerge" %in% colnames(calls)) {
        warning("Column 'nmerge' not found in 'calls'. Running mergeCalls with default parameters")
        calls <- mergeCalls(calls)
    }

    # The default information, we will fill it in the next steps
    res <- data.frame(id         = id,
                      chrom      = chrom,
                      strand     = strand,
                      pos        = pos,
                      p1.pos     = NA,
                      p1.score   = NA,
                      p1.score_w = NA,
                      p1.score_h = NA,
                      p1.class   = NA,
                      m1.pos     = NA,
                      m1.score   = NA,
                      m1.score_w = NA,
                      m1.score_h = NA,
                      m1.class   = NA,
                      p1.nmerge  = NA,
                      m1.nmerge  = NA,
                      dist       = NA,
                      dist.class = NA,
                      descr      = NA,
                      msg        = "")
    chrom <- as.character(chrom)
    strand <- as.character(strand)

    # Select nucleosomes nearby the given position
    start_in_bounds <- unlist(.mid(calls) > (pos - window), use.names=FALSE)
    end_in_bounds <- unlist(.mid(calls) < (pos + window), use.names=FALSE)
    sel <- start_in_bounds & end_in_bounds & space(calls) == chrom

    # Uncovered regions detection
    if (!is.null(cover)) {
        if ((pos-window) < 0 | (pos+window) > length(cover[[chrom]])) {
            res$msg <- paste(res$msg,
                             "WINDOW OUT OF CHROMOSOME BOUNDS",
                             sep=" | ")
        if (show.plot) {
            .doPlot(res, calls, cover, window, plot.limy)
        }
        return(res)

        } else {
            cov <- cover[[chrom]][(pos-window):(pos+window)]
            check <- sum(cov) > max.uncovered
            if (check) {
              res$msg <- paste(res$msg, "UNCOVERED REGION", sep=" | ")
              if (show.plot) {
                  .doPlot(res, calls, cover, window, plot.limy)
              }
            return(res)
            }
        }
    }

    # Check if there's any nucleosome around
    if (!any(which(sel))) {
        res$msg <- paste(res$msg, "NO NEARBY NUC.", sep=" | ")
        if(show.plot) {
            .doPlot(res, calls, cover, window, plot.limy)
        }
        return(res)
    }

    nearby <- calls[sel,]

    # Detect +1 nucleosome, strand sensitive
    if (strand=="+") {
        p1 <- nearby[.mid(nearby) > (pos - p1.max.downstream), ]
        if (nrow(p1) > 1) {
            p1 <- p1[.mid(p1) == min(.mid(p1)), ]
        }

    } else {  # - strand
        p1 <- nearby[.mid(nearby) < (pos + p1.max.downstream), ]
       if (nrow(p1) > 1) {
           p1 <- p1[.mid(p1) == max(.mid(p1)), ]
       }
    }

    # No +1 nucleosome upstream ref. point
    if (nrow(p1) < 1) {
        res$msg <- paste(res$msg, "+1 NUC MISSING", sep=" | ")
        res$descr <- "+1_missing"
        if (show.plot) {
            .doPlot(res, calls, cover, window, plot.limy)
        }
        return(res)
    }

    res$p1.pos <- .mid(p1)
    res$p1.score <- score(p1)
    res$p1.score_h <- p1$score_h
    res$p1.score_w <- p1$score_w
    res$p1.nmerge <- p1$nmerge

    # Check if +1 is a low complexity zone
    if (p1$nmerge > 3) {
        res$p1.class <- "F+"
        res$descr <- "+1_too_fuzzy"
        res$msg <- paste(res$msg, "+1 NUC. TOO FUZZY", sep=" | ")
        if (show.plot) {
            .doPlot(res, calls, cover, window, plot.limy)
        }
        return(res)
    }

    # Detect -1 nucleosome, strand sensitive
    if (strand == "+") {
        m1 <- nearby[start(p1) - .mid(nearby) > 0, ]
        if (nrow(m1) > 0) {
            m1 <- m1[start(m1) == max(start(m1)),]
            # dist <- start(p1) - end(m1)
            dist <- .mid(p1) - .mid(m1)
        }
    } else {
        m1 <- nearby[end(p1) - .mid(nearby) < 0, ]
        if (nrow(m1) > 0) {
            m1 <- m1[start(m1) == min(start(m1)),]
            # dist <- start(m1) - end(p1)
            dist <- .mid(p1) - .mid(m1)
        }
    }

    # No -1 nucleosome is detected
    if (nrow(m1) < 1) {
        res$msg <- paste(res$msg, "-1 NUC MISSING", sep=" | ")
        res$descr <- "-1_missing"
        res$m1.class <- "M"
        # if(show.plot) {
        #     .doPlot(res, calls, cover, window, plot.limy)
        # }
        # return(res)

    } else {
        res$m1.pos <- .mid(m1)
        res$m1.score <- score(m1)
        res$m1.score_h <- m1$score_h
        res$m1.score_w <- m1$score_w
        res$m1.nmerge <- m1$nmerge
        res$dist <- abs(dist)
    }

    # Evaluate class and add description
    if (is.na(res$p1.class)) {
        w_check <- p1$score_w > wp.thresh.score_w
        h_check <- p1$score_h > wp.thresh.score_h
        res$p1.class <- ifelse(w_check & h_check, "W", "F")
    }
    if (is.na(res$m1.class)) {
        w_check <- m1$score_w > wp.thresh.score_w
        h_check <- m1$score_h > wp.thresh.score_h
        res$m1.class = ifelse(w_check & h_check, "W", "F")
    }

    .gimmeDist <- function (x) {
         if (is.na(x)) {
             return("-")
         }
         if (x > open.thresh) {
             return("open")
         }
         if (x < 120) {
             return("overlap")
         }
         return("close")
    }

    res$dist.class <- sapply(res$dist, .gimmeDist)
    res$descr <- paste(res$m1.class, res$dist.class, res$p1.class, sep="-")
    res$descr[is.na(res$dist.class)] <- NA

    if(show.plot) {
        .doPlot(res, calls, cover, window, plot.limy)
    }

    # Remove " | " from the message begining (should be done after plotting)
    if (res$msg != "") {
        res$msg <- substr(res$msg, 4, nchar(res$msg))
    }

    return(res)
}

plotPatterns <- function(coverage, classif, window=300, ...)
{
    res <- classif #alias for c&p
    win <- window

    res2 <- res[!is.na(res$descr), ]  # rm na's

    # Get unique classes and assign colors
    classes <- unique(res2$descr)
    colors <- rainbow(length(classes))
    names(colors) <- classes

    # Plot each class
    for (class in classes) {

        # Get rows from current class and center nuc. +1
        tmp <- res2[res2$descr == class, ]
        tmp$p1.pos.zer <- tmp$p1.pos + tmp$pos - tmp$p1.pos

        # Calculate coverage, average and individual
        c1 <- coverAroundDF(coverage,
                            df        = tmp,
                            window    = win,
                            avg       = TRUE,
                            col.pos   = "p1.pos.zer",
                            col.names = "id")
        c1_ind <- coverAroundDF(coverage,
                                df        = tmp,
                                window    = win,
                                avg       = FALSE,
                                col.pos   = "p1.pos.zer",
                                col.names = "id")

        # Main plot
        plot(-win:win,
             c1,
             type="l",
             main=class,
             sub=paste(nrow(tmp), "genes"),
             col=colors[class],
             ...)

        # Sd calculation
        sds <- apply(c1_ind, 2, sd)
        c1_p_sd <- c1 + sds
        c1_m_sd <- c1 - sds

        # Sd lines
        lines(-win:win, c1_p_sd, lty=2, col="grey", lwd=2)
        lines(-win:win, c1_m_sd, lty=2, col="grey", lwd=2)
        abline(v=0, col="red")

        legend("bottomright",
               c("coverage", "+/- std dev"),
               lty=c(1, 2),
               col=c(colors[class], "grey"),
               bty="n")
    }
}