Initial commit

2016-01-13 10:23:54 +01:00
commit 9e33d6a180
44 changed files with 4080 additions and 0 deletions
--- a/R/mismatchplot.R
+++ b/R/mismatchplot.R
@@ -0,0 +1,106 @@
+#'@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)
+  
+}