106 lines
3.3 KiB
R
106 lines
3.3 KiB
R
#'@include ROBIBarcodes.R
|
|
#'@include logo.R
|
|
NULL
|
|
|
|
#' Draw a scatter plot of the reverse mismatches as a function of forward mismatches.
|
|
#'
|
|
#' The \code{mismatchplot} function draws a scatter plot of the number of mismatches
|
|
#' observed in an ecoPCR result for the reverse primer as a function of the mismatches
|
|
#' for the reverse primer. Each point for a pair (forward_mismatch,reverse_mismatch) is
|
|
#' drawn as a circle having a surface proportional to the aboundance of this pair in the
|
|
#' results. If a grouping factor is specified, then the circle is replaced by a pie chart.
|
|
#'
|
|
#' @param ecopcr an ecoPCR result data.frame as returned by the \code{\link{read.ecopcr.result}}
|
|
#' function.
|
|
#'
|
|
#' @param group a factor decribing classes amongst the amplicon described in the ecoPCR
|
|
#' result
|
|
#'
|
|
#' @param col a vector describing the colored used for the bubble or the pie charts
|
|
#'
|
|
#' @param legend a character vector describing the legend for each modality of the
|
|
#' grouping factor. By default the factor levels are used for the legend
|
|
#'
|
|
#' @param legend.cex the expension factor for the legend text
|
|
#'
|
|
#' @param inset the distance to the margin of the legend box (see the \code{\link{legend}}
|
|
#' documentation)
|
|
#'
|
|
#' @examples
|
|
#'
|
|
#' # Load the ROBITools library
|
|
#' library(ROBITools)
|
|
#'
|
|
#' # Load the default taxonomy
|
|
#' taxo = default.taxonomy()
|
|
#'
|
|
#' # Load the sample ecoPCR data file
|
|
#' data(GH.ecopcr)
|
|
#'
|
|
#' # Computes classes associated to each taxid
|
|
#' orders = as.factor(taxonatrank(taxo,GH.ecopcr$taxid,'order',name=T))
|
|
#'
|
|
#' # Plot the graph
|
|
#' mismatchplot(GH.ecopcr,group=orders)
|
|
#'
|
|
#' @seealso \code{\link{read.ecopcr.result}}
|
|
#' @author Eric Coissac
|
|
#' @export
|
|
mismatchplot = function(ecopcr,group=NULL,
|
|
col=NULL,legend=NULL,
|
|
legend.cex=0.7,inset=c(0.02,0.02)) {
|
|
|
|
maxforward_error = max(ecopcr$forward_mismatch)
|
|
maxreverse_error = max(ecopcr$reverse_mismatch)
|
|
maxerror=max(maxforward_error,maxreverse_error)
|
|
|
|
if (is.null(group))
|
|
group=factor(rep("all",dim(ecopcr)[1]))
|
|
else
|
|
group=as.factor(group)
|
|
|
|
if (is.null(legend))
|
|
legend = levels(group)
|
|
|
|
actualheight= maxerror + 1
|
|
actualwidth = maxerror + 1
|
|
|
|
if (length(levels(group)) > 1)
|
|
actualwidth = actualwidth + 2
|
|
|
|
whitepaper(actualwidth,actualheight,xmin=-0.5,ymin=-0.5,asp=1)
|
|
|
|
axis(1,at=0:maxerror,
|
|
labels=0:maxerror)
|
|
|
|
axis(2,at=0:maxerror,
|
|
labels=0:maxerror)
|
|
|
|
|
|
data = aggregate(group,by=list(forward=ecopcr$forward_mismatch,
|
|
reverse=ecopcr$reverse_mismatch),
|
|
table)
|
|
|
|
data <- data[rowSums(data[,c(-1,-2),drop=FALSE])>0, , drop=FALSE]
|
|
|
|
if (is.null(col))
|
|
col <- c("white", "lightblue", "mistyrose", "lightcyan",
|
|
"lavender", "cornsilk")
|
|
|
|
|
|
value=data[,c(-1,-2),drop=FALSE]
|
|
x = as.integer(data[,1])
|
|
y = as.integer(data[,2])
|
|
diam = sqrt(rowSums(value))
|
|
radius = diam / max(diam) / 2
|
|
|
|
hide = mapply(pie.xy,x,y,
|
|
data=lapply(1:(dim(value)[1]),function(y) value[y,]),
|
|
radius=radius,
|
|
label="",MoreArgs=list(col=col))
|
|
|
|
|
|
if (length(levels(group)) > 1)
|
|
legend('topright',legend=legend,fill=col, cex=legend.cex, inset=inset)
|
|
|
|
} |