Change the package path

R/contaslayer.R

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+#' @include 02_class_metabarcoding.data.R
+NULL
+
+#' Detects contaminants in metabarcoding data
+#' 
+#' Detects sequences/motus in a \code{\link{metabarcoding.data}} object
+#' for which frequencies over the entire dataset are maximum in negative controls and 
+#' hence, most likely to be contaminants. 
+#' 
+#' 
+#' @param x a \code{\link{metabarcoding.data}} object
+#' @param controls a vector of samples names where conta are suspected to be detected 
+#'                 (typically negative control names).
+#' @param clust a vector for grouping sequences. Default set to \code{NULL}.
+#'
+#' @return a vector containing the names of sequences identified as contaminants
+#'
+#' @examples
+#' 
+#' data(termes)
+#' termes.ok = termes[,colSums(termes$reads)>0]
+#' neg = rownames(termes.ok)[grep("r",rownames(termes.ok))]
+#' 
+#' #finds contaminants based on neg samples
+#' contaslayer(termes.ok, neg)
+#' 
+#' # extanding contamininant detection with grouping factor, 
+#' # typically obiclean/sumatra cluster or taxonomy membership
+#' contaslayer(termes.ok, neg, termes.ok$motus$scientific_name)
+#'   
+#' @seealso \code{\link{threshold}} for further trimming
+#' @author Lucie Zinger
+#' @export
+
+contaslayer = function(x,controls,clust=NULL){
+  
+  x.fcol = normalize(x, MARGIN=2)$reads
+  x.max = rownames(x.fcol[apply(x.fcol, 2, which.max),])
+  conta = colnames(x)[!is.na(match(x.max,controls))]
+  
+  if (length(clust)!=0) {
+    agg = data.frame(conta.id=colnames(x.fcol), clust)
+    conta.ext = agg$conta.id[which(!is.na(match( agg$clust, agg$clust[match(conta,agg$conta.id)])))]
+    return(as.vector(conta.ext))
+  } 
+  else {
+    return(conta)
+  }
+}