diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..cd92261
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,4 @@
+.Rproj.user
+.Rhistory
+.RData
+loopbenchmark.R
diff --git a/R/aggregate.R b/R/aggregate.R
index 586eaa6..07eaca8 100644
--- a/R/aggregate.R
+++ b/R/aggregate.R
@@ -101,9 +101,10 @@ aggregate.metabarcoding.data=function(x, by, FUN,...,
 			  m = matrix(as.character(x[[n]]))
 			  dim(m)=df
 			}
-			else
+			else {
 			  m = x[[n]]
-
+        isfact=FALSE
+		  }
       aggr.args = list(m,by=by,FUN=f,simplify=FALSE)
 			lagr = do.call(aggregate,aggr.args)
 			lagr = as.factor.or.matrix(lagr[,-(1:ncat),drop=FALSE])
@@ -182,15 +183,15 @@ aggregate.metabarcoding.data=function(x, by, FUN,...,
     
     for (n in ln) {
 			f = layers[[n]]
-      
-      if (is.factor(x[[n]])){
+      isfact=is.factor(x[[n]])
+      if (isfact){
 			  isfact = TRUE
         lf = levels(x[[n]])
         df = dim(x[[n]])
         m = matrix(as.character(x[[n]]))
         dim(m)=df
       }
-      else
+      else 
           m = x[[n]]
 
       aggr.args = list(t(m),by=by,FUN=f,simplify=FALSE)
diff --git a/man/ROBITools-package.Rd b/man/ROBITools-package.Rd
new file mode 100644
index 0000000..c22ac8a
--- /dev/null
+++ b/man/ROBITools-package.Rd
@@ -0,0 +1,34 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/ROBITools.R
+\docType{package}
+\name{ROBITools-package}
+\alias{ROBITools-package}
+\alias{ROBITools}
+\title{A package to manipulate DNA metabarcoding data.}
+\description{
+A package to manipulate DNA metabarcoding data.
+}
+\details{
+This package was written as a following of the OBITools.
+
+\tabular{ll}{
+ Package: \tab ROBITools\cr
+ Type: \tab Package\cr
+ Version: \tab 0.1\cr
+ Date: \tab 2013-06-27\cr
+ License: \tab CeCILL 2.0\cr
+ LazyLoad: \tab yes\cr
+}
+}
+\references{
+http://metabarcoding.org/obitools
+}
+\author{
+Frederic Boyer
+
+Aurelie Bonin
+
+Lucie Zinger
+
+Eric Coissac
+}
diff --git a/man/addS3Class.Rd b/man/addS3Class.Rd
new file mode 100644
index 0000000..b86726a
--- /dev/null
+++ b/man/addS3Class.Rd
@@ -0,0 +1,41 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/s3objects.R
+\name{addS3Class}
+\alias{addS3Class}
+\title{Adds a class into the class hierarchie attribute.}
+\usage{
+addS3Class(object, classname)
+}
+\arguments{
+\item{object}{the object to modify}
+
+\item{classname}{the name of the new class}
+}
+\value{
+the object given as parametter casted to the new
+        class
+}
+\description{
+\code{addS3Class} adds a new class name to the vector
+of class associated to the object. This the way to
+assign an object to an S3 class. \code{addS3Class} add
+the new class name in front of the class vector
+}
+\note{
+for efficiency purpose no check is done on the input
+      parametters
+}
+\examples{
+x = c(1,3,2,5)
+x = addS3Class(x,"my.vector")
+class(x)
+
+}
+\seealso{
+\code{\link{rmS3Class}}
+}
+\author{
+Eric Coissac
+}
+\keyword{function}
+\keyword{system}
diff --git a/man/const-threshold-mask-methods.Rd b/man/const-threshold-mask-methods.Rd
new file mode 100644
index 0000000..a16570f
--- /dev/null
+++ b/man/const-threshold-mask-methods.Rd
@@ -0,0 +1,52 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/metabarcoding_threshold.R
+\docType{methods}
+\name{const.threshold.mask,metabarcoding.data-method}
+\alias{const.threshold.mask,metabarcoding.data-method}
+\alias{const.threshold.mask-methods,metabarcoding.data}
+\title{Computes a constant thresold mask for filtering read aboundancies.}
+\usage{
+\S4method{const.threshold.mask}{metabarcoding.data}(data, MARGIN,
+  threshold = 0.01, operator = "<")
+}
+\arguments{
+\item{data}{The \code{\linkS4class{metabarcoding.data}} instance
+on normalisation have to be computed.}
+
+\item{MARGIN}{Indicates if the sums have to be computed across 
+samples or motus. 
+Allowed values are :
+\itemize{
+  \item{'sample' or 1} for computing sum across samples
+  \item{'motu' or 2} for computing sum across motus
+  }}
+
+\item{threshold}{a numeric value between 0 and 1 indicating which part of 
+the signal must be conserved. Default value is setup to
+0.01 (1% of the normalized signal).}
+
+\item{operator}{is a logical comparison operator.}
+}
+\value{
+A logical matrix usable for selecting cell in the read aboundancy matrix.
+}
+\description{
+The method \code{const.threshold.mask} of the class \code{\linkS4class{metabarcoding.data}}
+computes a logical matrix of the same size than the read matrix of the data parameter.
+Each cell of this matrix contains a \code{TRUE} or a \code{FALSE} value according to the
+relationship existing between the read abondancy and the global theshold.
+}
+\details{
+(computed value) = (normalized read aboundancy) operator (threshold value)
+
+for a cell in the result matrix, \code{(normalized read aboundancy)} is extracted from the read layer
+after normalization.
+\code{operator} is a comparaison operator and \code{(threshold value)} is estimated with the
+\code{\link{theshold}} method.
+}
+\seealso{
+\code{\linkS4class{metabarcoding.data}}, \code{\link{threshold.mask}}, \code{\link{normalize}}
+}
+\author{
+Aurelie Bonin
+}
diff --git a/man/contaslayer.Rd b/man/contaslayer.Rd
new file mode 100644
index 0000000..cffde6f
--- /dev/null
+++ b/man/contaslayer.Rd
@@ -0,0 +1,44 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/contaslayer.R
+\name{contaslayer}
+\alias{contaslayer}
+\title{Detects contaminants in metabarcoding data}
+\usage{
+contaslayer(x, controls, clust = NULL)
+}
+\arguments{
+\item{x}{a \code{\link{metabarcoding.data}} object}
+
+\item{controls}{a vector of samples names where conta are suspected to be detected 
+(typically negative control names).}
+
+\item{clust}{a vector for grouping sequences. Default set to \code{NULL}.}
+}
+\value{
+a vector containing the names of sequences identified as contaminants
+}
+\description{
+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.
+}
+\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
+}
diff --git a/man/createS3Class.Rd b/man/createS3Class.Rd
new file mode 100644
index 0000000..54fdb03
--- /dev/null
+++ b/man/createS3Class.Rd
@@ -0,0 +1,50 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/s3objects.R
+\name{createS3Class}
+\alias{createS3Class}
+\title{create basic functions to manipulate a new S3 class}
+\usage{
+createS3Class(classname)
+}
+\arguments{
+\item{classname}{a \code{character string} indicating the name
+of the new class.}
+}
+\description{
+createS3Class function create in the \code{package:ROBITools}
+environment an \code{is.xxx} function and an \code{as.xxx} function
+allowing to test if an abject belong the class \code{xxx} and to add
+the class \code{xxx} to the class list of an object. \code{xxx} is a 
+generic class name that is specified through the \code{classname}
+argument of the function.
+}
+\note{
+Take care that the new functions are created in the 
+\code{package:ROBITools} environment.
+}
+\examples{
+
+# Create a new S3 class named mynewclass
+createS3Class('mynewclass')
+
+#create a new vector object
+x=c(1,4,6)
+
+# test if it belongs the new class, that is false
+is.mynewclass(x)
+
+# Associate x to the new class
+as.mynewclass(x)
+
+# test again if x belongs the new class, that is now true
+is.mynewclass(x)
+
+}
+\seealso{
+\code{\link{rmS3Class}}
+}
+\author{
+Eric Coissac
+}
+\keyword{function}
+\keyword{system}
diff --git a/man/dbtree.Rd b/man/dbtree.Rd
new file mode 100644
index 0000000..923acab
--- /dev/null
+++ b/man/dbtree.Rd
@@ -0,0 +1,52 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/taxoDBtree.R
+\name{dbtree}
+\alias{dbtree}
+\title{Construct a taxonomic tree from a list of taxa}
+\usage{
+dbtree(x)
+}
+\arguments{
+\item{x}{a table containing the taxonomic path of the references. Typically an output from get.classic.taxonomy}
+}
+\value{
+g a directed graph displaying the taxonomy hierarchy of the input data. Stored in a \code{\link{igraph}} object 
+        where the taxonomic ranks of the vertices are added to the vertices attributes
+}
+\description{
+Construct a graph from a table containing the taxonomic path of sequences
+}
+\examples{
+
+data(termes)
+
+taxo=default.taxonomy()
+
+termes.taxo.table = get.classic.taxonomy(termes, taxo, "taxid")
+head(termes.taxo.table)
+
+graph.tax.termes = dbtree(termes.taxo.table[,1:7])
+library(igraph)
+
+#plot the tree
+coord = layout.reingold.tilford(graph.tax.termes, root=1, circular=F)
+v.cex = as.factor(V(graph.tax.termes)$rank)
+levels(v.cex) = match(levels(v.cex), colnames(termes.taxo.table))
+plot(graph.tax.termes, vertex.size=1, vertex.label.cex=2*(as.numeric(as.vector(v.cex))^-1), edge.arrow.size=0, layout=coord)
+
+
+#Vizualization with sequence counts
+tax.count = log10(colSums(termes$reads)[match(as.vector(V(graph.tax.termes)$name), termes$motus$scientific_name)])
+tax.count[is.na(tax.count)|tax.count<0] = 0.01
+V(graph.tax.termes)$count = unname(tax.count)
+
+plot(graph.tax.termes, vertex.size=V(graph.tax.termes)$count, vertex.label.cex=2*(as.numeric(as.vector(v.cex))^-1), edge.arrow.size=0, layout=coord)
+
+  
+}
+\seealso{
+\code{\link{get.classic.taxonomy}}
+}
+\author{
+Lucie Zinger
+}
diff --git a/man/dist.center.group.Rd b/man/dist.center.group.Rd
new file mode 100644
index 0000000..85a1177
--- /dev/null
+++ b/man/dist.center.group.Rd
@@ -0,0 +1,32 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mstat.R
+\name{dist.center.group}
+\alias{dist.center.group}
+\title{Builds the list of sample groups included in a circle around a central sample}
+\usage{
+dist.center.group(dtable, radius, center = TRUE)
+}
+\arguments{
+\item{dtable}{a distance table between samples as 
+computed by \code{\link{dist.grid}}}
+
+\item{radius}{the radius of the circle}
+
+\item{center}{a \code{logical} value indicating if the center of
+the group must be included in the group}
+}
+\value{
+a list of vectors containing the labels of the group members
+}
+\description{
+Builds the list of sample groups included in a circle around a central sample
+}
+\examples{
+data(termes)
+termes.ok = termes[,colSums(termes$reads)>0]
+pos = expand.grid(1:3 * 10,1:7 * 10)
+labels = rownames(termes.ok)
+d = dist.grid(pos[,1],pos[2],labels)
+groups = dist.center.group(d,20)
+
+}
diff --git a/man/dist.clique.group.Rd b/man/dist.clique.group.Rd
new file mode 100644
index 0000000..43363f0
--- /dev/null
+++ b/man/dist.clique.group.Rd
@@ -0,0 +1,31 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mstat.R
+\name{dist.clique.group}
+\alias{dist.clique.group}
+\title{Builds the list of sample groups including samples closest than a define distance}
+\usage{
+dist.clique.group(dtable, dmax, center = True)
+}
+\arguments{
+\item{dtable}{a distance table between samples as 
+computed by \code{\link{dist.grid}}}
+
+\item{dmax}{the maximum distance between two samples}
+}
+\value{
+a list of vectors containing the labels of the group members
+}
+\description{
+A graph is build by applying the threshold \code{dmax} to the distance matrix
+A group is a clique max in this graph. Consequently all member pairs of a group
+are distant by less or equal to \code{dmax}.
+}
+\examples{
+data(termes)
+termes.ok = termes[,colSums(termes$reads)>0]
+pos = expand.grid(1:3 * 10,1:7 * 10)
+labels = rownames(termes.ok)
+d = dist.grid(pos[,1],pos[2],labels)
+groups = dist.clique.group(d,20)
+
+}
diff --git a/man/dist.grid.Rd b/man/dist.grid.Rd
new file mode 100644
index 0000000..ffbc173
--- /dev/null
+++ b/man/dist.grid.Rd
@@ -0,0 +1,32 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mstat.R
+\name{dist.grid}
+\alias{dist.grid}
+\title{Computes the pairwise distance matrix as a data.frame where}
+\usage{
+dist.grid(x, y, labels = NULL)
+}
+\arguments{
+\item{x}{a vector for the X coordinates}
+
+\item{y}{a vector for the Y coordinates}
+
+\item{labels}{a vector with the sample names}
+}
+\value{
+a data.frame instance of three columns
+   - a : The label of the first sample
+   - b : The label of the second sample
+   - dist : The euclidian distance beween sample a and b
+}
+\description{
+Computes the pairwise distance matrix as a data.frame where
+}
+\examples{
+data(termes)
+termes.ok = termes[,colSums(termes$reads)>0]
+pos = expand.grid(1:3 * 10,1:7 * 10)
+labels = rownames(termes.ok)
+d = dist.grid(pos[,1],pos[2],labels)
+
+}
diff --git a/man/dm.univariate.Rd b/man/dm.univariate.Rd
new file mode 100644
index 0000000..b9c5196
--- /dev/null
+++ b/man/dm.univariate.Rd
@@ -0,0 +1,39 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mstat.R
+\name{dm.univariate}
+\alias{dm.univariate}
+\title{Simulate null distribion of the M statistics by Monte-Carlo}
+\usage{
+dm.univariate(w, groups, resampling = 100)
+}
+\arguments{
+\item{w}{the weigth matrix indicating the presence probability of each motu
+in each samples. Each line corresponds to a sample and each column
+to a MOTU. \code{rownames} of the \code{w} matrix must be the sample
+names.}
+
+\item{groups}{the list of considered groups as computed by the \code{\link{dist.center.group}}
+function}
+
+\item{resampling}{the number of simulation to establish the null distribution}
+}
+\value{
+a matrix of M score under the null hypothesis of random distribution of MOTUs
+        with a MOTUs per line and a culumn per simulation
+}
+\description{
+Computes the null empirical distribution of the M statistics
+by shuffling MOTUs among location.
+}
+\examples{
+      
+data(termes)
+termes.ok = termes[,colSums(termes$reads)>0]
+pos = expand.grid(1:3 * 10,1:7 * 10)
+labels = rownames(termes.ok)
+d = dist.grid(pos[,1],pos[2],labels)
+groups = dist.center.group(d,20)
+w = m.weight(termes.ok)
+dnull = dm.univariate(w,groups)
+
+}
diff --git a/man/double-open-brace-methods.Rd b/man/double-open-brace-methods.Rd
new file mode 100644
index 0000000..a1e2b4b
--- /dev/null
+++ b/man/double-open-brace-methods.Rd
@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/layers.metabarcoding.R
+\docType{methods}
+\name{[[,metabarcoding.data-method}
+\alias{[[,metabarcoding.data-method}
+\alias{double-open-brace-methods,metabarcoding.data}
+\title{Returns the a layer associated to a \code{\link{metabarcoding.data}}}
+\usage{
+\method{[[}{unmutable}(x,i)
+}
+\arguments{
+\item{x}{a \code{\link{metabarcoding.data}} instance}
+}
+\value{
+matrix or a factor.
+}
+\description{
+[[ operator Extracts a layer
+attached to a \code{\link{metabarcoding.data}} instance.
+}
diff --git a/man/extracts-obiclean-methods.Rd b/man/extracts-obiclean-methods.Rd
new file mode 100644
index 0000000..a63cd4e
--- /dev/null
+++ b/man/extracts-obiclean-methods.Rd
@@ -0,0 +1,48 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/obiclean.R
+\docType{methods}
+\name{extracts.obiclean,metabarcoding.data-method}
+\alias{extracts.obiclean,metabarcoding.data-method}
+\alias{extracts.obiclean-methods,metabarcoding.data}
+\title{Extracts the obiclean results}
+\usage{
+\S4method{extracts.obiclean}{metabarcoding.data}(obj)
+}
+\arguments{
+\item{obj}{the \code{\linkS4class{metabarcoding.data}} to analyze}
+}
+\value{
+the modified \code{\linkS4class{metabarcoding.data}} instance
+}
+\description{
+The method \code{extracts.obiclean} of the class \code{\linkS4class{metabarcoding.data}}
+extracts \code{obiclean} results from the MOTUs descriptions include in the 
+\code{\linkS4class{metabarcoding.data}} instance. 
+When an \code{obitab} file is imported using the \code{\link{import.metabarcoding.data}}
+if \code{obiclean} results are present in the file they are stored in the 
+\code{motu} data.frame. By calling this methods, MOTU descriptors describing 
+the \code{obiclean} status are moved to a set of layers.
+}
+\examples{
+
+# load termite data set from the ROBITools sample data
+data(termes)
+
+# shows the initial list of layer names
+layer.names(t)
+
+# extracts the obiclean status
+termes = extracts.obiclean(termes)
+
+# shows the name of the newly created layers
+layer.names(t)
+
+
+
+}
+\seealso{
+\code{\linkS4class{metabarcoding.data}}, \code{\link{threshold.mask}}, \code{\link{normalize}}
+}
+\author{
+Eric Coissac
+}
diff --git a/man/extrapol.freq.Rd b/man/extrapol.freq.Rd
new file mode 100644
index 0000000..e4189b3
--- /dev/null
+++ b/man/extrapol.freq.Rd
@@ -0,0 +1,65 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/distrib.extrapol.R
+\name{extrapol.freq}
+\alias{extrapol.freq}
+\title{Read frequencies krigging}
+\usage{
+extrapol.freq(x, min.coord, max.coord, grid.grain = 100, coords, otus.table,
+  cutoff = 0.001, return.metabarcoding.data = FALSE)
+}
+\arguments{
+\item{x}{a vector or matrix from a row-normalized read table 
+\code{\link{metabarcoding.data}} object}
+
+\item{min.coord}{a vector of length = 2 indicating the minimum values of x and y
+coordinates to be used for the predicted grid}
+
+\item{max.coord}{a vector of length = 2 indicating the maximum values of x and y
+coordinates to be used for the predicted grid}
+
+\item{grid.grain}{an integer indicating the resolution (i.e. nb of subpoints) in x and y
+coordinates required for the predicted grid}
+
+\item{coords}{a dataframe containing the x and y coordinates of the abundances 
+from x to be extrapolated.}
+
+\item{otus.table}{a motus data.frame containing motus informations of x}
+
+\item{cutoff}{a cutoff below which abundances are set to 0. 
+This threshold also determines the value to be added to 0 values for log10 
+transformation}
+
+\item{return.metabarcoding.data}{if \code{TRUE}, returns a \code{\link{metabarcoding.data}} object. Default is \code{FALSE}}
+}
+\value{
+either a dataframe or a S3 object with a structure similar to \code{\link{metabarcoding.data}} object. 
+        The number of samples corresponds to the predicted points.
+        The two last columns (if \code{return.metabarcoding.data==F}) or sample data.frame contains x y coordinates of the predicted grid
+        The all but last two columns (if \code{return.metabarcoding.data==F}) or read matrix contains the predicted log10 transformed relative abundances 
+        instead of reads counts
+        If \code{return.metabarcoding.data==F} the motus data.frame contains the motus informations from x
+}
+\description{
+Extrapolates read frequencies from a \code{\link{metabarcoding.data}} object in space for a finer resolution
+}
+\examples{
+
+data(termes)
+#Create dummy spatial coordinates
+attr(termes, "samples")[c("x", "y")] = expand.grid(1:7,1:3)
+
+#compute frequencies
+attr(termes, "layers")[["reads.freq"]] = normalize(termes, MARGIN=1)$reads
+
+# Getting extrapolations
+termes.pred = extrapol.freq(attr(termes, "layers")[["reads.freq"]], min.coord=c(1,1), max.coord=c(7,3), 
+                            grid.grain=100,termes$samples[,c("x", "y")], termes$motus, cutoff=1e-3)
+
+head(termes.pred$reads)
+}
+\seealso{
+\code{\link{map.extrapol.freq}} as well as \code{sp} and \code{gstat} packages
+}
+\author{
+Lucie Zinger
+}
diff --git a/man/get.classic.taxonomy.Rd b/man/get.classic.taxonomy.Rd
new file mode 100644
index 0000000..2023b6d
--- /dev/null
+++ b/man/get.classic.taxonomy.Rd
@@ -0,0 +1,43 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/taxonomy_classic_table.R
+\name{get.classic.taxonomy}
+\alias{get.classic.taxonomy}
+\title{Get classical taxonomy format}
+\usage{
+get.classic.taxonomy(x, taxonomy, coltaxid)
+}
+\arguments{
+\item{x}{a \code{\link{metabarcoding.data}} object}
+
+\item{taxonomy}{a instance of \code{\linkS4class{taxonomy.obitools}}}
+
+\item{coltaxid}{a the name of the column containing taxids to be used for creating classical taxonomic description}
+}
+\value{
+returns a data.frame with the classical taxonomic description ("kingdom", "phylum", "class", "order", "family", "genus", "species"), as well as
+        sequence taxonomic assignment rank and scientific name for each sequences stored in the \code{\link{metabarcoding.data}} object
+}
+\description{
+Creates a table with the classical taxonomic description (from phylum to species)
+}
+\examples{
+
+data(termes)
+
+taxo=default.taxonomy()
+
+termes.taxo.table = get.classic.taxonomy(termes, taxo, "taxid")
+head(termes.taxo.table)
+
+attr(termes, "motus") = data.frame(termes$motus, termes.taxo.table)
+
+  
+}
+\seealso{
+\code{\linkS4class{taxonomy.obitools}}, and methods \code{\link{species}},\code{\link{genus}}, \code{\link{family}},\code{\link{kingdom}},
+         \code{\link{superkingdom}},\code{\link{taxonatrank}}, \code{\link{taxonmicank}}
+}
+\author{
+Lucie Zinger
+}
+\keyword{taxonomy}
diff --git a/man/import.metabarcoding.data.Rd b/man/import.metabarcoding.data.Rd
new file mode 100644
index 0000000..e1535fa
--- /dev/null
+++ b/man/import.metabarcoding.data.Rd
@@ -0,0 +1,51 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/import.metabarcoding.R
+\name{import.metabarcoding.data}
+\alias{import.metabarcoding.data}
+\title{Read a data file produced by the \code{obitab} command}
+\usage{
+import.metabarcoding.data(file, sep = "\\t", sample = "sample",
+  sample.sep = "\\\\.", attribute = ":")
+}
+\arguments{
+\item{file}{a string containing the file name of the obitab file.}
+
+\item{sep}{Column separator in the obitab file. 
+The default separator is the tabulation.}
+
+\item{sample}{A regular expression allowing to identify columns 
+from the file describing abundances of sequences per sample}
+
+\item{sample.sep}{Separator between combined sample name.}
+
+\item{attribute}{Separator used to split between sample 'tag' and sample name.}
+}
+\value{
+a \code{\link{metabarcoding.data}} instance
+}
+\description{
+Read a data file issued from the conversion of a \strong{fasta} 
+file to a tabular file by the \code{obitab} command of the 
+\strong{OBITools} package
+}
+\examples{
+require(ROBITools)
+
+\dontshow{# switch the working directory to the data package directory}
+\dontshow{setwd(system.file("extdata", package="ROBITools"))}
+
+# read the termes.tab file
+termes=import.metabarcoding.data('termes.tab')
+
+# print the number of samples and motus described in the file
+dim(termes)
+  
+}
+\seealso{
+\code{\link{metabarcoding.data}}
+}
+\author{
+Eric Coissac
+}
+\keyword{DNA}
+\keyword{metabarcoding}
diff --git a/man/import.ngsfilter.data.Rd b/man/import.ngsfilter.data.Rd
new file mode 100644
index 0000000..6c8475f
--- /dev/null
+++ b/man/import.ngsfilter.data.Rd
@@ -0,0 +1,45 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/import.ngsfilter.R
+\name{import.ngsfilter.data}
+\alias{import.ngsfilter.data}
+\title{Read ngsfilter text file}
+\usage{
+import.ngsfilter.data(file, platewell = NULL)
+}
+\arguments{
+\item{file}{a string containing the file name for the \code{ngsfilter} command.}
+
+\item{platewell}{a string corresponding to the tag used for storing the sample location
+in the PCR plate. Should be of the form "nbPlate_Well" (e.g. "01_A02").
+Default is \code{NULL}}
+}
+\value{
+\code{\link{import.ngsfilter.data}} returns a \code{\link{data.frame}} instance
+}
+\description{
+Reads  the text file used for assigning reads to samples with the
+ \code{ngsfilter} command of the \strong{OBITools} package.
+}
+\examples{
+\dontshow{# switch the working directory to the data package directory}
+\dontshow{setwd(system.file("extdata", package="ROBITools"))}
+
+data(termes)
+
+# reading the termes_ngsfilt.txt file
+termes.ngs=import.ngsfilter.data('termes_ngsfilt.txt', platewell="position")
+
+# including ngsfilter data into termes data
+attr(termes, "samples") = termes.ngs[rownames(termes),]
+
+colnames(termes$samples)
+  
+}
+\seealso{
+\code{\link{import.metabarcoding.data}} and \code{\link{read.obitab}} for other methods of data importation
+}
+\author{
+Lucie Zinger
+}
+\keyword{DNA}
+\keyword{metabarcoding}
diff --git a/man/initialize-methods.Rd b/man/initialize-methods.Rd
new file mode 100644
index 0000000..0918e25
--- /dev/null
+++ b/man/initialize-methods.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/02_class_metabarcoding.data.R
+\docType{methods}
+\name{initialize,metabarcoding.data-method}
+\alias{initialize,metabarcoding.data-method}
+\alias{initialize-methods,metabarcoding.data}
+\title{metabarcoding.data constructor}
+\usage{
+\S4method{initialize}{metabarcoding.data}(.Object, reads, samples, motus,
+  taxonomy = NULL, taxid = NULL, sample.margin = NA, layers = list())
+}
+\description{
+metabarcoding.data constructor
+}
diff --git a/man/layer.names-methods.Rd b/man/layer.names-methods.Rd
new file mode 100644
index 0000000..d2886ef
--- /dev/null
+++ b/man/layer.names-methods.Rd
@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/layers.metabarcoding.R
+\docType{methods}
+\name{layer.names,metabarcoding.data-method}
+\alias{layer.names,metabarcoding.data-method}
+\alias{layer.names-methods,metabarcoding.data}
+\title{Returns the names of all the layers}
+\usage{
+\S4method{layer.names}{metabarcoding.data}(obj)
+}
+\arguments{
+\item{obj}{a \code{\link{metabarcoding.data}} instance}
+}
+\value{
+a vector of type \code{character} containing the
+         list of all the layer names.
+}
+\description{
+\code{layer.names} extracts the list of all the layer
+names attached to a \code{\link{metabarcoding.data}} instance.
+}
diff --git a/man/m.bivariate.Rd b/man/m.bivariate.Rd
new file mode 100644
index 0000000..a9aa5e8
--- /dev/null
+++ b/man/m.bivariate.Rd
@@ -0,0 +1,54 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mstat.R
+\name{m.bivariate}
+\alias{m.bivariate}
+\title{Computes the bivariate M statistics}
+\usage{
+m.bivariate(w1, w2 = NULL, groups)
+}
+\arguments{
+\item{w1}{the weigth matrix indicating the presence probability of each motu
+used as focus species in each samples. Each line corresponds to a sample and each column
+to a MOTU. \code{rownames} of the \code{w} matrix must be the sample
+names. It is nice but not mandatory if the \code{colnames} refer to the MOTU id.}
+
+\item{w2}{the weigth matrix indicating the presence probability of each motu
+used as target species in each samples. Each line corresponds to a sample and each column
+to a MOTU. \code{rownames} of the \code{w} matrix must be the sample
+names. It is nice but not mandatory if the \code{colnames} refer to the MOTU id.
+if \code{w2} is not set, w1 is also used as target species. in this case the diagonal
+of the matrix return contains the univariate M statistic for the diferent species.}
+
+\item{groups}{the list of considered groups as computed by the \code{\link{dist.center.group}}
+function}
+}
+\value{
+a matrix of M bivariate statistics with one focus species by row and one target species 
+        by columns If \code{w2} is not specified the diagonal of the matrix is equal to the univariate
+        M statistic of the corresponding species.
+}
+\description{
+The function computes the bivariate M statiscics for a set of target species around a set of
+focus species.
+}
+\examples{
+data(termes)
+termes.ok = termes[,colSums(termes$reads)>0]
+pos = expand.grid(1:3 * 10,1:7 * 10)
+labels = rownames(termes.ok)
+d = dist.grid(pos[,1],pos[2],labels)
+groups = dist.center.group(d,20)
+w = m.weight(termes.ok)
+m = m.bivariate(w,groups)
+
+}
+\references{
+Marcon, E., Puech, F., and Traissac, S. (2012). 
+            Characterizing the relative spatial structure of point patterns. 
+            International Journal of Ecology, 2012.
+}
+\seealso{
+\code{\link{dist.center.group}}
+
+\code{\link{m.weight}}
+}
diff --git a/man/m.univariate.Rd b/man/m.univariate.Rd
new file mode 100644
index 0000000..11306a2
--- /dev/null
+++ b/man/m.univariate.Rd
@@ -0,0 +1,41 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mstat.R
+\name{m.univariate}
+\alias{m.univariate}
+\title{Computes the univariate M statistics}
+\usage{
+m.univariate(w, groups)
+}
+\arguments{
+\item{w}{the weigth matrix indicating the presence probability of each motu
+in each samples. Each line corresponds to a sample and each column
+to a MOTU. \code{rownames} of the \code{w} matrix must be the sample
+names.  It is nice but not mandatory if the \code{colnames} refer to the MOTU id.}
+
+\item{groups}{the list of considered groups as computed by the \code{\link{dist.center.group}}
+function}
+}
+\description{
+Computes the univariate M statistics
+}
+\examples{
+data(termes)
+termes.ok = termes[,colSums(termes$reads)>0]
+pos = expand.grid(1:3 * 10,1:7 * 10)
+labels = rownames(termes.ok)
+d = dist.grid(pos[,1],pos[2],labels)
+groups = dist.center.group(d,20)
+w = m.weight(termes.ok)
+m = m.univariate(w,groups)
+
+}
+\references{
+Marcon, E., Puech, F., and Traissac, S. (2012). 
+            Characterizing the relative spatial structure of point patterns. 
+            International Journal of Ecology, 2012.
+}
+\seealso{
+\code{\link{dist.center.group}}
+
+\code{\link{m.weight}}
+}
diff --git a/man/m.univariate.test.Rd b/man/m.univariate.test.Rd
new file mode 100644
index 0000000..26c6a67
--- /dev/null
+++ b/man/m.univariate.test.Rd
@@ -0,0 +1,47 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mstat.R
+\name{m.univariate.test}
+\alias{m.univariate.test}
+\title{Test the significance of the M statistics by Monte-Carlo}
+\usage{
+m.univariate.test(w, groups, resampling = 100, alternative = "two.sided")
+}
+\arguments{
+\item{w}{the weigth matrix indicating the presence probability of each motu
+in each samples. Each line corresponds to a sample and each column
+to a MOTU. \code{rownames} of the \code{w} matrix must be the sample
+names.}
+
+\item{groups}{the list of considered groups as computed by the \code{\link{dist.center.group}}
+function}
+
+\item{resampling}{the number of simulation to establish the null distribution}
+
+\item{alternative}{a character value in \code{c('two.sided','less','greater')}
+- two.sided : the m stat is check against the two side of the empirical
+              M distribution
+- less : test if the M stat is lesser than the M observed in the the empirical
+              M distribution (exlusion hypothesis)
+- greater : test if the M stat is greater than the M observed in the the empirical
+              M distribution (aggregation hypothesis)}
+}
+\value{
+a vector of p.value with an attribute \code{m.stat} containing the actual M stat
+        for each MOTUs
+}
+\description{
+Computes computes the p.value the M statistics asociated to a MOTU
+by shuffling MOTUs among location.
+}
+\examples{
+      
+data(termes)
+termes.ok = termes[,colSums(termes$reads)>0]
+pos = expand.grid(1:3 * 10,1:7 * 10)
+labels = rownames(termes.ok)
+d = dist.grid(pos[,1],pos[2],labels)
+groups = dist.center.group(d,20)
+w = m.weight(termes.ok)
+pval = m.univariate.test(w,groups)
+
+}
diff --git a/man/m.weight.Rd b/man/m.weight.Rd
new file mode 100644
index 0000000..af8a56e
--- /dev/null
+++ b/man/m.weight.Rd
@@ -0,0 +1,25 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mstat.R
+\name{m.weight}
+\alias{m.weight}
+\title{Computes a weigth matrix from a \code{\linkS4class{metabarcoding.data}}}
+\usage{
+m.weight(data)
+}
+\arguments{
+\item{data}{a \code{\linkS4class{metabarcoding.data}} instance}
+}
+\value{
+a weight matrix usable for M statistics
+}
+\description{
+The weight can be considered as a propability of presence of a MOTU in a 
+given sample. This function defines this probability as the fraction of
+the maximal occurrence frequency over all samples.
+}
+\examples{
+data(termes)
+termes.ok = termes[,colSums(termes$reads)>0]
+w = m.weight(termes.ok)
+
+}
diff --git a/man/map.extrapol.freq.Rd b/man/map.extrapol.freq.Rd
new file mode 100644
index 0000000..1f30663
--- /dev/null
+++ b/man/map.extrapol.freq.Rd
@@ -0,0 +1,61 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/distrib.extrapol.R
+\name{map.extrapol.freq}
+\alias{map.extrapol.freq}
+\title{Maps of krigged log10-transformed frequencies}
+\usage{
+map.extrapol.freq(x, path = NULL, col.name = NULL, index, cutoff = 0.001,
+  add.points = NULL, adj = 4)
+}
+\arguments{
+\item{x}{an extrapol.freq output}
+
+\item{path}{the path of the folder to export the map. Default is \code{NULL} and map is printed in Rplot/quartz}
+
+\item{index}{an integer indicating column number of the motu/sequence to be plotted.}
+
+\item{cutoff}{lower motu frequency accepted to consider motu abundance as different
+from 0. Should be the same than the one used in extrapol.freq}
+
+\item{add.points}{a 3-column data.frame containing factor levels and associated x and y coordinates
+to be added to the map. Typically taxa observed in the field.}
+
+\item{adj}{a value used for adjusting text position in the map. Default is \code{4}}
+
+\item{col.names}{a vector containing the names of the columns to be used for defining the file name. Typically
+the column names containing the taxonomic information and/or sequence/motus id.}
+}
+\value{
+a map/png file displaying motus distribution.
+}
+\description{
+Maps the output of extrapol.freq
+}
+\examples{
+
+data(termes)
+attr(termes, "samples")[c("x", "y")] = expand.grid(1:7,1:3)
+
+#compute frequencies
+attr(termes, "layers")[["reads.freq"]] = normalize(termes, MARGIN=1)$reads
+
+# Getting extrapolations
+termes.pred = extrapol.freq(attr(termes, "layers")[["reads.freq"]], 
+grid.grain=100,termes$samples[,c("x", "y")], termes$motus, cutoff=1e-3)
+
+#mapping the distribution of the 3 most abundant sequences (caution, mfrow does not work for lattice's levelplot)
+map.extrapol.freq(termes.pred, path=NULL, col.name=NULL, 1, cutoff=1e-3)
+map.extrapol.freq(termes.pred, path=NULL, col.name=NULL, 2, cutoff=1e-3)
+map.extrapol.freq(termes.pred, path=NULL, col.name=NULL, 3, cutoff=1e-3)
+
+#dummy observationnal data
+termes.obs = data.frame(x=c(2,3,5), y=c(2.7,2,2.6), taxa = rep("Isoptera Apicotermitinae", 3))
+map.extrapol.freq(termes.pred, path=NULL, col.name=NULL, 3, cutoff=1e-3, add.points=termes.obs)
+
+}
+\seealso{
+\code{\link{extrapol.freq}}, and \code{levelplot} from \code{lattice} package
+}
+\author{
+Lucie Zinger
+}
diff --git a/man/marginalsum-methods.Rd b/man/marginalsum-methods.Rd
new file mode 100644
index 0000000..d31fdd5
--- /dev/null
+++ b/man/marginalsum-methods.Rd
@@ -0,0 +1,50 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/metabarcoding_threshold.R
+\docType{methods}
+\name{marginalsum,metabarcoding.data-method}
+\alias{marginalsum,metabarcoding.data-method}
+\alias{marginalsum-methods,metabarcoding.data}
+\title{Computes marginal sums over read counts.}
+\usage{
+\S4method{marginalsum}{metabarcoding.data}(data, MARGIN = "sample",
+  na.rm = FALSE)
+}
+\arguments{
+\item{data}{The \code{\linkS4class{metabarcoding.data}} instance
+on which marginal sums have to be computed.}
+
+\item{MARGIN}{Indicates if the sums have to be computed across 
+samples or motus. 
+Allowed values are :
+\itemize{
+  \item{'sample' or 1} for computing sum across samples
+  \item{'motu' or 2} for computing sum across motus
+  }}
+
+\item{na.rm}{Logical. Should missing values be omitted from the 
+calculations?}
+}
+\value{
+Returns the vector of marginal sums as a \code{numeric} vector
+}
+\description{
+Method \code{marginalsum} computes marginal sums over read counts of
+a \code{\link{metabarcoding.data}} instance.
+}
+\examples{
+# load termite data set from the ROBITools sample data
+data(termes)
+
+# Computes marginal sums per sample
+ssum = marginalsum(termes,MARGIN="sample")
+
+# Computes marginal sums per MOTU
+msum = marginalsum(termes,MARGIN="motu")
+
+}
+\seealso{
+\code{\linkS4class{metabarcoding.data}}
+}
+\author{
+Aurelie Bonin
+}
diff --git a/man/metabarcoding-data-class.Rd b/man/metabarcoding-data-class.Rd
new file mode 100644
index 0000000..c585c4d
--- /dev/null
+++ b/man/metabarcoding-data-class.Rd
@@ -0,0 +1,68 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/02_class_metabarcoding.data.R
+\docType{class}
+\name{metabarcoding.data}
+\alias{metabarcoding.data}
+\title{DNA metabarcoding experiment description class}
+\description{
+A S4 class describing a DNA metabarcoding experiment. It groups
+three data frames describing samples, motus and occurrences of 
+MOTUs per sample
+}
+\section{Slots}{
+ 
+ \describe{
+   \item{\code{reads}:}{Matrix of class \code{"numeric"},  
+                        containing the counts of reads per samples
+                        \itemize{
+                          \item{1 samples per line}
+                          \item{1 sequence per column}
+                        }
+                       }
+                       
+   \item{\code{samples}:}{Object of class \code{"data.frame"}, describing samples
+                        \itemize{
+                          \item{1 samples per line}
+                          \item{1 property per column}
+                        }
+                      }
+                      
+   \item{\code{motus}:}{Object of class \code{"data.frame"}, describing MOTUs (sequences)
+                        \itemize{
+                          \item{1 MOTU per line}
+                          \item{1 property per column}
+                        }
+                      }
+                      
+   \item{\code{layers}:}{Object of class \code{"list"}, containing a set of data layers 
+                         linking motus and samples. Each element of the list is a matrix
+                         of the same size than the \code{read} slot with
+                        \itemize{
+                          \item{1 samples per line}
+                          \item{1 sequence per column}
+                        }
+                      }
+       
+   \item{\code{scount}:}{Object of class \code{"integer"}, containing the count of sample}             
+       
+   \item{\code{mcount}:}{Object of class \code{"integer"}, containing the count of MOTUs}             
+       
+   \item{\code{sample.margin}:}{Vector of class \code{"numeric"},  describing the total count of 
+                         sequence per sample. By default this slot is set by applying sum
+                        to the reads data.frame lines}             
+
+   \item{\code{taxonomy}:}{Object of class \code{"taxonomy.obitools"}, linking the DNA metabarcoding
+                           experiment to a taxonomy}             
+       
+   \item{\code{taxid}:}{Vector of class \code{"character"}, list of MOTUs' attributes to manage as taxid}             
+ }
+}
+
+\seealso{
+\code{\link{taxonomy.obitools}},
+}
+\author{
+Eric Coissac
+}
+\keyword{DNA}
+\keyword{metabarcoding}
diff --git a/man/motu-methods.Rd b/man/motu-methods.Rd
new file mode 100644
index 0000000..96958b9
--- /dev/null
+++ b/man/motu-methods.Rd
@@ -0,0 +1,34 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/02_class_metabarcoding.data.R
+\docType{methods}
+\name{motus,metabarcoding.data-method}
+\alias{motus,metabarcoding.data-method}
+\alias{motu-methods,metabarcoding.data}
+\title{Extracts the MOTU descriptions \code{data.frame}}
+\usage{
+\S4method{motus}{metabarcoding.data}(obj)
+}
+\arguments{
+\item{obj}{a \code{\link{metabarcoding.data}} instance}
+}
+\value{
+a data.frame containing data about MOTU
+}
+\description{
+Extract the MOTUs description \code{data.frame} from a 
+\code{\link{metabarcoding.data}} instance.
+}
+\examples{
+# load termite data set from the ROBITools sample data
+data(termes)
+
+# Extract the data.frame describing MOTUs
+d = motus(termes)
+
+head(d)
+
+}
+\seealso{
+\code{\link{metabarcoding.data}},
+         \code{\link{reads}}, \code{\link{samples}}
+}
diff --git a/man/normalize-methods.Rd b/man/normalize-methods.Rd
new file mode 100644
index 0000000..ecb3b18
--- /dev/null
+++ b/man/normalize-methods.Rd
@@ -0,0 +1,57 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/metabarcoding_threshold.R
+\docType{methods}
+\name{normalize,metabarcoding.data-method}
+\alias{normalize,metabarcoding.data-method}
+\alias{normalize-methods,metabarcoding.data}
+\title{Normalizes read counts by sample or by MOTU.}
+\usage{
+\S4method{normalize}{metabarcoding.data}(data, MARGIN = "sample",
+  as.matrix = FALSE)
+}
+\arguments{
+\item{data}{The \code{\linkS4class{metabarcoding.data}} instance
+on normalisation have to be computed.}
+
+\item{MARGIN}{Indicates if the sums have to be computed across 
+samples or motus. 
+Allowed values are :
+\itemize{
+  \item{'sample' or 1} for computing sum across samples
+  \item{'motu' or 2} for computing sum across motus
+  }}
+
+\item{as.matrix}{Logical indicating if the normalized aboundancies
+must be returned as a simple \code{matrix} (TRUE) or as a new
+instance of the \code{\linkS4class{metabarcoding.data}} class
+(FALSE, the default case).}
+}
+\value{
+Returns a new instance of \code{\linkS4class{metabarcoding.data}}
+        or a \code{numeric} matrix according to the \code{return.as.matrix}
+        parameter.
+}
+\description{
+Method \code{normalize} computes a normalized read aboundancy matrix
+(relative frequency matrix) of a \code{\link{metabarcoding.data}} instance.
+Normalization can be done according aboundancies per sample or per MOTU.
+}
+\examples{
+# load termite data set from the ROBITools sample data
+data(termes)
+
+# Computes normalized aboundancies per sample
+termes.norm = normalize(termes,MARGIN="sample")
+
+# Computes normalized aboundancies per sample and
+# stores the result as a new layer into the thermes
+# structure
+termes$normalized = normalize(termes,MARGIN="sample",as.matrix=TRUE)
+
+}
+\seealso{
+\code{\linkS4class{metabarcoding.data}}
+}
+\author{
+Aurelie Bonin
+}
diff --git a/man/plot.PCRplate.Rd b/man/plot.PCRplate.Rd
new file mode 100644
index 0000000..76710b0
--- /dev/null
+++ b/man/plot.PCRplate.Rd
@@ -0,0 +1,65 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plot.PCRplate.R
+\name{plot.PCRplate}
+\alias{plot.PCRplate}
+\title{Plot PCR plates}
+\usage{
+\method{plot}{PCRplate}(x, samples = NULL, col = "cyan2", different = T,
+  ...)
+}
+\arguments{
+\item{x}{a \code{\link{metabarcoding.data}} object}
+
+\item{samples}{a character vector containing names of problematic samples. Default is \code{NULL}}
+
+\item{different}{a boolean indicating whether different tags where used in forward and reverse to identify samples. Default is \code{TRUE}}
+
+\item{...}{arguments ot be passed to methods, such as graphical parameters}
+}
+\value{
+\code{\link{plot.PCRplate}} returns a plot displaying no more than 4 PCR plates, with problematic sample localization
+}
+\description{
+Plots samples localization in PCR plates, and points out problematic samples if provided.
+}
+\examples{
+\dontshow{# switch the working directory to the data package directory}
+\dontshow{setwd(system.file("extdata", package="ROBITools"))}
+
+data(termes)
+
+# reading the termes_ngsfilt.txt file
+termes.ngs=import.ngsfilter.data('termes_ngsfilt.txt', platewell="position")
+
+# including ngsfilter data into termes data
+attr(termes, "samples") = termes.ngs[rownames(termes),]
+
+#plot PCR plate plan
+col = rep("green", nrow(termes))
+col[grep("r", rownames(termes))] = "red"
+plot.PCRplate(termes, col=col)
+
+#highlighting location of samples with low identification score
+
+#low quality taxonomic assignements identification
+library(plotrix)
+weighted.hist(termes$motus$best_identity, colSums(termes$reads), breaks = 20, ylab = "Nb reads", xlab = "Ecotag scores", xaxis=F)
+axis(1, labels = T)
+lowqual.seq = rownames(termes$motus)[termes$motus$best_identity < 0.7]
+
+#identification and localization (in PCR plate) of samples with high proportions of low quality taxonomic assignements
+termes.freq= normalize(termes, MARGIN=1)$reads
+hist(log10(rowSums(termes.freq[,lowqual.seq]) + 1e-05), breaks = 20, xlab = "Prop low quality reads")
+lowqual.sample = rownames(termes)[log10(rowSums(termes.freq[, lowqual.seq]) + 1e-05) > -0.5]
+
+plot.PCRplate(termes, lowqual.sample, col=col)
+  
+}
+\seealso{
+\code{\link{import.metabarcoding.data}}
+}
+\author{
+Lucie Zinger
+}
+\keyword{DNA}
+\keyword{metabarcoding}
diff --git a/man/plot.seqinsample.Rd b/man/plot.seqinsample.Rd
new file mode 100644
index 0000000..1c87f9c
--- /dev/null
+++ b/man/plot.seqinsample.Rd
@@ -0,0 +1,45 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plot.seqinsample.R
+\name{plot.seqinsample}
+\alias{plot.seqinsample}
+\title{Plot sequence abundance in samples}
+\usage{
+\method{plot}{seqinsample}(x, seqset, seqtype, controls = NULL)
+}
+\arguments{
+\item{x}{a \code{\link{metabarcoding.data}} object}
+
+\item{seqset}{a vetcor with sequences names}
+
+\item{seqtype}{a string indicating what type of sequences are displayed}
+
+\item{controls}{a vector indicating the negative controls names in the x object.
+Default is \code{NULL}}
+}
+\value{
+returns a plot with the log10 transformed relative porportion of 
+        selected MOTUs in each samples. If the number of samples is > 96,
+        then the plot is displayed in 4 panels
+}
+\description{
+Plots relative abundances of a set of sequences in all samples (log10 transformed)
+}
+\examples{
+
+data(termes)
+
+seqset = rownames(termes$motus)[which(termes$motus$genus_name=="Anoplotermes")]
+plot.seqinsample(termes, seqset, "Anoplotermes")
+
+controls = rownames(termes)[grep("r", rownames(termes))]
+seqset = rownames(termes$motus)[which(termes$motus$best_identity<0.7)]
+plot.seqinsample(termes, seqset, "Not assigned", controls)
+
+}
+\seealso{
+\code{\linkS4class{taxonomy.obitools}}, and method \code{\link{taxonmicank}}
+}
+\author{
+Lucie Zinger
+}
+\keyword{metabarcoding}
diff --git a/man/read-methods.Rd b/man/read-methods.Rd
new file mode 100644
index 0000000..f3510bc
--- /dev/null
+++ b/man/read-methods.Rd
@@ -0,0 +1,37 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/02_class_metabarcoding.data.R
+\docType{methods}
+\name{reads,metabarcoding.data-method}
+\alias{reads,metabarcoding.data-method}
+\alias{read-methods,metabarcoding.data}
+\title{Extracts the matrix describing MOTUs abondances}
+\usage{
+\S4method{reads}{metabarcoding.data}(obj)
+}
+\arguments{
+\item{obj}{a \code{\link{metabarcoding.data}} instance}
+}
+\value{
+a matrix containing data about reads
+}
+\description{
+Extract the the matrix describing MOTUs abondances (read counts) 
+from a \code{\link{metabarcoding.data}} instance.
+}
+\examples{
+# load termite data set from the ROBITools sample data
+data(termes)
+
+# Extract the matrix describing MOTUs abondances
+d = reads(termes)
+
+head(d)
+
+}
+\seealso{
+\code{\link{metabarcoding.data}},
+         \code{\link{motus}}, \code{\link{samples}}
+}
+\author{
+Eric Coissac
+}
diff --git a/man/read.ngsfilter.Rd b/man/read.ngsfilter.Rd
new file mode 100644
index 0000000..57f9c1c
--- /dev/null
+++ b/man/read.ngsfilter.Rd
@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/read.ngsfilter.R
+\name{read.ngsfilter}
+\alias{read.ngsfilter}
+\title{Read an OBITools ngsfilter file}
+\usage{
+read.ngsfilter(filename, decimal = ".", as.is = !stringsAsFactors,
+  stringsAsFactors = default.stringsAsFactors())
+}
+\description{
+Reads a ngsfilter file as formatted for the OBITools. For now, needs to be tab delimited till the "F" column. 
+Any additionnal information needs to be space delimited.
+}
+\seealso{
+\code{\link{import.metabarcoding.data}}
+}
+\author{
+Lucie Zinger
+}
+\keyword{data}
+\keyword{import}
diff --git a/man/read.obitab.Rd b/man/read.obitab.Rd
new file mode 100644
index 0000000..77c77c8
--- /dev/null
+++ b/man/read.obitab.Rd
@@ -0,0 +1,40 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/read.obitab.R
+\name{read.obitab}
+\alias{read.obitab}
+\title{Reads a data file produced by the obitab command}
+\usage{
+read.obitab(filename, sep = "\\t")
+}
+\arguments{
+\item{sep}{Column separator in the obitab file. 
+The default separator is the tabulation.}
+
+\item{file}{a string containing the file name of the obitab file.}
+}
+\value{
+a \code{data.frame} instance containing the obitab file
+}
+\description{
+Read a data file issued from the convertion of a fasta 
+file to a tabular file by the obitab command
+}
+\examples{
+require(ROBITools)
+
+\dontshow{# switch the working directory to the data package directory}
+\dontshow{setwd(system.file("extdata", package="ROBITools"))}
+
+# read the termes.tab file
+termes=read.obitab('termes.tab')
+
+# print the dimensions of the data.frame
+dim(termes)
+  
+}
+\seealso{
+\code{\link{import.metabarcoding.data}}
+}
+\author{
+Eric Coissac
+}
diff --git a/man/rmS3Class.Rd b/man/rmS3Class.Rd
new file mode 100644
index 0000000..c35c4cf
--- /dev/null
+++ b/man/rmS3Class.Rd
@@ -0,0 +1,41 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/s3objects.R
+\name{rmS3Class}
+\alias{rmS3Class}
+\title{Removes a class from the class hierarchie attribute.}
+\usage{
+rmS3Class(object, classname)
+}
+\arguments{
+\item{object}{the object to modify}
+
+\item{classname}{the name of the class to remove}
+}
+\value{
+the object given as parametter.
+}
+\description{
+\code{rmS3Class} removes a class name from the vector
+of class associated to the object. This the way to
+remove the association between an object and a S3 class.
+}
+\note{
+for efficiency purpose no check is done on the input
+      parametters
+}
+\examples{
+x = c(1,3,2,5)
+x = addS3Class(x,"my.vector")
+class(x)
+x = rmS3Class(x,"my.vector")
+class(x)
+
+}
+\seealso{
+\code{\link{addS3Class}}
+}
+\author{
+Eric Coissac
+}
+\keyword{function}
+\keyword{system}
diff --git a/man/samples-methods.Rd b/man/samples-methods.Rd
new file mode 100644
index 0000000..d3783ed
--- /dev/null
+++ b/man/samples-methods.Rd
@@ -0,0 +1,37 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/02_class_metabarcoding.data.R
+\docType{methods}
+\name{samples,metabarcoding.data-method}
+\alias{samples,metabarcoding.data-method}
+\alias{samples-methods,metabarcoding.data}
+\title{Extracts the samples description data.frame}
+\usage{
+\S4method{samples}{metabarcoding.data}(obj)
+}
+\arguments{
+\item{obj}{a \code{\link{metabarcoding.data}} instance}
+}
+\value{
+a data.frame containing data about sample
+}
+\description{
+Extract the sample description data.frame from a 
+\code{\link{metabarcoding.data}} instance.
+}
+\examples{
+# load termite data set from the ROBITools sample data
+data(termes)
+
+# Extract the data frame describing samples
+d = samples(termes)
+
+head(d)
+
+}
+\seealso{
+\code{\link{metabarcoding.data}},
+         \code{\link{motus}}, \code{\link{reads}}
+}
+\author{
+Eric Coissac
+}
diff --git a/man/summary.taxores.Rd b/man/summary.taxores.Rd
new file mode 100644
index 0000000..9b5d4df
--- /dev/null
+++ b/man/summary.taxores.Rd
@@ -0,0 +1,43 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/taxonomic.resolution.R
+\name{summary.taxores}
+\alias{summary.taxores}
+\title{Dataset taxonomic resolution summary.}
+\usage{
+\method{summary}{taxores}(x, colranks, colscores, thresh = 0.7)
+}
+\arguments{
+\item{x}{a \code{\link{metabarcoding.data}} object}
+
+\item{colranks}{a string indicating column name where ranks are stored in \code{x}}
+
+\item{colscores}{a string indicating column name where taxonomic identification scores are stored in \code{x}}
+
+\item{thresh}{a threshold for defining at which taxonomic identification scores a sequence can be considered as "not assigned". 
+Default is \code{0.7}}
+}
+\value{
+returns a data.frame and piecharts of the number/proportion of MOTUs/reads assigned to each taxonomic levels
+}
+\description{
+Summarizes the taxonomic relution of reads and MOTUs over the entire dataset
+}
+\examples{
+
+data(termes)
+taxo=default.taxonomy()
+
+termes.taxo.table = get.classic.taxonomy(termes, taxo, "taxid")
+attr(termes, "motus") = data.frame(termes$motus, termes.taxo.table)
+attr(termes, "motus")["count"] = colSums(termes$reads)
+
+summary.taxores(termes, "taxonomic_rank_ok","best_identity")
+
+}
+\seealso{
+\code{\linkS4class{taxonomy.obitools}}, and method \code{\link{taxonmicank}}
+}
+\author{
+Lucie Zinger
+}
+\keyword{taxonomy}
diff --git a/man/taxo.decider.Rd b/man/taxo.decider.Rd
new file mode 100644
index 0000000..803cd2e
--- /dev/null
+++ b/man/taxo.decider.Rd
@@ -0,0 +1,60 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/choose.taxonomy.R
+\name{taxo.decider}
+\alias{taxo.decider}
+\title{Choose between databases for taxonomic classifications}
+\usage{
+taxo.decider(x, taxonomy, dbrank, thresh = 0.95)
+}
+\arguments{
+\item{x}{a \code{\link{metabarcoding.data}} object}
+
+\item{taxonomy}{a \code{\linkS4class{taxonomy.obitools}} instance}
+
+\item{dbrank}{string or vector indicating reference database names ranked by order of preference}
+
+\item{thresh}{a best_identity threshold for applying priority. Default is \code{0.95}}
+}
+\value{
+returns a data.frame with the refined taxonomic assignement and classic taxonomy description.
+}
+\description{
+Chooses a sequence taxonomic assignment in order of preference for the different 
+reference databases that have been used when the assignment is above a certain threshold
+}
+\examples{
+
+data(termes)
+
+taxo=default.taxonomy()
+
+#create artificial taxonomic assignments
+attr(termes, "motus")["best_identity:DB1"] = sample(seq(0.5,1,0.001),size=nrow(termes$motus), replace=T)
+attr(termes, "motus")["best_identity:DB2"] = sample(seq(0.5,1,0.001),size=nrow(termes$motus), replace=T)
+attr(termes, "motus")["best_identity:DB3"] = sample(seq(0.5,1,0.001),size=nrow(termes$motus), replace=T)
+attr(termes, "motus")["taxid_by_db:DB1"] = termes$motus$taxid
+attr(termes, "motus")["taxid_by_db:DB2"] = sample(termes$motus$taxid,size=nrow(termes$motus), replace=F)
+attr(termes, "motus")["taxid_by_db:DB3"] = sample(termes$motus$taxid,size=nrow(termes$motus), replace=F)
+
+#Run taxo.decider
+termes.ok = taxo.decider(termes, taxo, "DB2", 0.95)
+head(termes.ok$motus[union(grep("DB",  colnames(termes.ok$motus)), grep("_ok", colnames(termes.ok$motus)))])
+
+termes.ok = taxo.decider(termes, taxo, c("DB3", "DB1"), 0.95)
+head(termes.ok$motus[union(grep("DB",  colnames(termes.ok$motus)), grep("_ok", colnames(termes.ok$motus)))])
+
+#Quick look at the enhancement in taxonomic assignements
+par(mfrow=c(1,4))
+for(i in grep("best_identity.", colnames(termes.ok$motus))){
+hist(termes.ok$motus[,i], breaks=20, ylim=c(1,21), main=colnames(termes.ok$motus)[i], xlab="assignment score")
+}
+    
+}
+\seealso{
+\code{\linkS4class{taxonomy.obitools}}, and methods \code{\link{species}},\code{\link{genus}}, \code{\link{family}},\code{\link{kingdom}},
+         \code{\link{superkingdom}},\code{\link{taxonatrank}}, \code{\link{taxonmicank}}
+}
+\author{
+Lucie Zinger
+}
+\keyword{taxonomy}
diff --git a/man/threshold-mask-methods.Rd b/man/threshold-mask-methods.Rd
new file mode 100644
index 0000000..50f643b
--- /dev/null
+++ b/man/threshold-mask-methods.Rd
@@ -0,0 +1,52 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/metabarcoding_threshold.R
+\docType{methods}
+\name{threshold.mask,metabarcoding.data-method}
+\alias{threshold.mask,metabarcoding.data-method}
+\alias{threshold.mask-methods,metabarcoding.data}
+\title{Computes a cumulatif thresold mask for filtering read aboundancies.}
+\usage{
+\S4method{threshold.mask}{metabarcoding.data}(data, MARGIN, threshold = 0.97,
+  operator = "<")
+}
+\arguments{
+\item{data}{The \code{\linkS4class{metabarcoding.data}} instance
+on normalisation have to be computed.}
+
+\item{MARGIN}{Indicates if the sums have to be computed across 
+samples or motus. 
+Allowed values are :
+\itemize{
+  \item{'sample' or 1} for computing sum across samples
+  \item{'motu' or 2} for computing sum across motus
+  }}
+
+\item{threshold}{a numeric value between 0 and 1 indicating which part of 
+the signal must be conserved. Default value is setup to
+0.97 (97% of the total signal).}
+
+\item{operator}{is a logical comparison operator.}
+}
+\value{
+A logical matrix usable for selecting cell in the read aboundancy matrix.
+}
+\description{
+The method \code{threshold.mask} of the class \code{\linkS4class{metabarcoding.data}}
+computes a logical matrix of the same size than the read matrix of the data parameter.
+Each cell of this matrix contains a \code{TRUE} or a \code{FALSE} value according to the
+relationship existing between the read abondancy and the corresponding theshold as computed
+by the \code{\link{theshold}} method.
+}
+\details{
+(computed value) = (read aboundancy) operator (threshold value)
+
+for a cell in the result matrix, \code{(read aboundancy)} is extracted from the read layer.
+\code{operator} is a comparaison operator and \code{(threshold value)} is estimated with the
+\code{\link{theshold}} method.
+}
+\seealso{
+\code{\linkS4class{metabarcoding.data}}, \code{\link{threshold.mask}}, \code{\link{threshold}}
+}
+\author{
+Aurelie Bonin
+}
diff --git a/man/threshold-methods.Rd b/man/threshold-methods.Rd
new file mode 100644
index 0000000..1ff9acb
--- /dev/null
+++ b/man/threshold-methods.Rd
@@ -0,0 +1,55 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/metabarcoding_threshold.R
+\docType{methods}
+\name{threshold,metabarcoding.data-method}
+\alias{threshold,metabarcoding.data-method}
+\alias{threshold-methods,metabarcoding.data}
+\title{Compute the cumulative threshold of read aboundances.}
+\usage{
+\S4method{threshold}{metabarcoding.data}(data, MARGIN = "sample",
+  threshold = 0.97)
+}
+\arguments{
+\item{data}{The \code{\linkS4class{metabarcoding.data}} instance
+on normalisation have to be computed.}
+
+\item{MARGIN}{Indicates if the sums have to be computed across 
+samples or motus. 
+Allowed values are :
+\itemize{
+  \item{'sample' or 1} for computing sum across samples
+  \item{'motu' or 2} for computing sum across motus
+  }}
+
+\item{threshold}{a numeric value between 0 and 1 indicating which part of 
+the signal must be conserved. Default value is setup to
+0.97 (97% of the total signal).}
+}
+\value{
+a numeric vector containing the limit aboundancy to consider for
+        each sample or each MOTU according to the value of the \code{MARGIN} 
+        parameter.
+}
+\description{
+The method \code{threshold} of the class \code{\linkS4class{metabarcoding.data}}
+computes the thresold to be used for conserving just a part of the global
+signal. This thresold is computed by ranking aboundances by decreasing order.
+The cululative sums of these ranked abondencies are computed and the aboundance
+corresponding to the first sum greater than the threshold is returned as result.
+}
+\examples{
+# load termite data set from the ROBITools sample data
+data(termes)
+
+# computes threshold value to used for keep 95\% of 
+# the reads per MOTU
+
+t = threshold(termes,MARGIN='motu',threshold=0.95)
+ 
+}
+\seealso{
+\code{\linkS4class{metabarcoding.data}}, \code{\link{threshold.mask}}
+}
+\author{
+Aurelie Bonin
+}
diff --git a/src/.gitignore b/src/.gitignore
new file mode 100644
index 0000000..656836b
--- /dev/null
+++ b/src/.gitignore
@@ -0,0 +1,2 @@
+ROBITools.so
+*.o