@@ -1,6 +1,6 @@

 Package: metagenomeSeq

 Title: Statistical analysis for sparse high-throughput sequencing

-Version: 1.5.44

+Version: 1.5.45

 Date: 2013-03-09

 Author: Joseph Nathaniel Paulson, Mihai Pop, Hector Corrada Bravo

 Maintainer: Joseph N. Paulson <jpaulson@umiacs.umd.edu>

@@ -15,7 +15,7 @@ License: Artistic-2.0

 Depends: R(>= 3.0), Biobase, limma, matrixStats, methods, RColorBrewer,

         gplots

 Suggests: annotate, biom, vegan, knitr

-Collate: 'aggregateByTaxonomy.R' 'aggregateM.R' 'allClasses.R'

+Collate: 'aggregateByTaxonomy.R' 'allClasses.R'

         'biom2MRexperiment.R' 'calculateEffectiveSamples.R' 'cumNorm.R'

         'cumNormStat.R' 'cumNormStatFast.R' 'cumNormMat.R'

         'doCountMStep.R' 'doZeroMStep.R' 'doEStep.R' 'exportMat.R'

@@ -10,7 +10,6 @@ exportMethods(

 )

 export(

-aggregateM,

 aggregateByTaxonomy,

 aggTax,

 biom2MRexperiment,

@@ -1,5 +1,5 @@

 #' @name aggregateByTaxonomy

-#' @title Aggregates a MRexperiment object by a particular taxonomic level.

+#' @title Aggregates a MRexperiment object or counts matrix to a particular level.

 #' 

 #' Using the featureData information in the MRexperiment, calling aggregateByTaxonomy on a

 #' MRexperiment and a particular featureData column (i.e. 'genus') will aggregate counts

@@ -22,8 +22,9 @@

 #' 

 #' # not run

 #' # aggregateByTaxonomy(mouseData,lvl="genus",norm=TRUE,aggfun=colMedians)

+#' # aggTax(mouseData,lvl='phylum',norm=FALSE,aggfun=colSums)

 #' 

-aggregateByTaxonomy<-function(obj,lvl,alternate=FALSE,norm=TRUE,log=FALSE,aggfun = colSums,sl=1000,out="MRexperiment"){

+aggregateByTaxonomy<-function(obj,lvl,alternate=FALSE,norm=FALSE,log=FALSE,aggfun = colSums,sl=1000,out="MRexperiment"){

 	if(class(obj)=="MRexperiment"){

 		mat = MRcounts(obj,norm=norm,log=log,sl=sl)

 		levels = as.character(fData(obj)[,lvl])

@@ -64,13 +65,13 @@ aggregateByTaxonomy<-function(obj,lvl,alternate=FALSE,norm=TRUE,log=FALSE,aggfun

 		} else {

 			newObj = newMRexperiment(newMat,featureData=taxa)

 		}

-		warning("\n\nThe output here are aggregated (normalized?) counts.\n

-			Check default parameters for all metagenomeSeq functions so as not to renormalize.")

+		warning("\n\nThe output here are aggregated counts.\n

+			Check default parameters for all metagenomeSeq functions and consider normalization.")

 		return(newObj)

 	}

 }

 #' @rdname aggregateByTaxonomy

 #' @export

-aggTax<-function(obj,lvl,alternate=FALSE,norm=TRUE,log=FALSE,aggfun = colSums,sl=1000,out='MRexperiment'){

+aggTax<-function(obj,lvl,alternate=FALSE,norm=FALSE,log=FALSE,aggfun = colSums,sl=1000,out='MRexperiment'){

 	aggregateByTaxonomy(obj,lvl,alternate=alternate,norm=norm,log=log,aggfun = aggfun,sl=sl,out=out)

 }

\ No newline at end of file

deleted file mode 100644

@@ -1,58 +0,0 @@

-#' Aggregates counts by a particular classification.

-#' 

-#' This function takes a MRexperiment object of data at a particular level with

-#' feature information allowing for aggregation of counts to a particular

-#' level. This method assumes taxa begin at the highest level and continue to

-#' the current level, reverse assumes taxa begin at the lowest level.

-#' 

-#' 

-#' @param obj A MRexperiment object.

-#' @param lvl The level to go up (numeric, 1,2,3).

-#' @param taxa A vector of taxa annotations with splits

-#' @param split The way character strings in taxa in the obj are split.

-#' @return Updated object with counts aggregated to the various taxanomic

-#' levels.

-aggregateM <-

-function(obj,taxa,lvl,split=";"){

-

-	tmp<-strsplit(taxa,split=split);

-	nrows = length(taxa);

-    cnts  = MRcounts(obj)

-	

-	maxName=max(sapply(tmp,length))

-	

-	featureMat<-array("NA",dim=c(nrows,maxName));

-	

-	for(i in 1:nrows){

-		for(j in 1:length(tmp[[i]])){

-			featureMat[i,j]=tmp[[i]][j]

-			}

-	}

-	

-	tt = sapply(1:nrows,function(i){

-		   t = featureMat[i,1]

-		   for(j in 2:lvl){

-				t = paste(t,featureMat[i,j],sep=";")

-		   }

-		   t})

-	

-	newTaxa<-unique(tt);

-    newCountMat<-array(0,dim=c(length(newTaxa),ncol(cnts)));

-

-    colnames(newCountMat)<-sampleNames(obj)

-	rownames(newCountMat)<-newTaxa;	

-	

-	for(i in 1:length(newTaxa)){

-		if(length(which(tt==newTaxa[i]))<2){

-			newCountMat[rownames(newCountMat)==newTaxa[i],]=as.matrix(cnts[which(tt==newTaxa[i]),],nr=1)

-		}else{

-			newCountMat[rownames(newCountMat)==newTaxa[i],]=colSums(cnts[which(tt==newTaxa[i]),])

-		}

-	}

-	

-	taxa<-newTaxa;

-	assayData(obj)<-newCountMat;

-	validObject(obj)

-

-	return(obj)

-}

@@ -1,17 +1,17 @@

 \name{aggregateByTaxonomy}

 \alias{aggTax}

 \alias{aggregateByTaxonomy}

-\title{Aggregates a MRexperiment object by a particular taxonomic level.

+\title{Aggregates a MRexperiment object or counts matrix to a particular level.

 Using the featureData information in the MRexperiment, calling aggregateByTaxonomy on a

 MRexperiment and a particular featureData column (i.e. 'genus') will aggregate counts

 to the desired level using the aggfun function (default colSums). Possible aggfun alternatives

 include colMeans and colMedians.}

 \usage{

-aggregateByTaxonomy(obj, lvl, alternate = FALSE, norm = TRUE, log = FALSE,

-  aggfun = colSums, sl = 1000, out = "MRexperiment")

+aggregateByTaxonomy(obj, lvl, alternate = FALSE, norm = FALSE,

+  log = FALSE, aggfun = colSums, sl = 1000, out = "MRexperiment")

-aggTax(obj, lvl, alternate = FALSE, norm = TRUE, log = FALSE,

+aggTax(obj, lvl, alternate = FALSE, norm = FALSE, log = FALSE,

   aggfun = colSums, sl = 1000, out = "MRexperiment")

 }

 \arguments{

@@ -39,8 +39,8 @@ aggTax(obj, lvl, alternate = FALSE, norm = TRUE, log = FALSE,

 An aggregated count matrix.

 }

 \description{

-Aggregates a MRexperiment object by a particular taxonomic

-level.

+Aggregates a MRexperiment object or counts matrix to a

+particular level.

 Using the featureData information in the MRexperiment,

 calling aggregateByTaxonomy on a MRexperiment and a

@@ -52,5 +52,6 @@ colMeans and colMedians.

 \examples{

 # not run

 # aggregateByTaxonomy(mouseData,lvl="genus",norm=TRUE,aggfun=colMedians)

+# aggTax(mouseData,lvl='phylum',norm=FALSE,aggfun=colSums)

 }

deleted file mode 100644

@@ -1,29 +0,0 @@

-\name{aggregateM}

-\alias{aggregateM}

-\title{Aggregates counts by a particular classification.}

-\usage{

-aggregateM(obj, taxa, lvl, split = ";")

-}

-\arguments{

-  \item{obj}{A MRexperiment object.}

-

-  \item{lvl}{The level to go up (numeric, 1,2,3).}

-

-  \item{taxa}{A vector of taxa annotations with splits}

-

-  \item{split}{The way character strings in taxa in the obj

-  are split.}

-}

-\value{

-Updated object with counts aggregated to the various

-taxanomic levels.

-}

-\description{

-This function takes a MRexperiment object of data at a

-particular level with feature information allowing for

-aggregation of counts to a particular level. This method

-assumes taxa begin at the highest level and continue to the

-current level, reverse assumes taxa begin at the lowest

-level.

-}

-