1. metagenomeSeq
  2. Commit 4144cbaa045b510dfc8d83d50068e7e6a0d7c81f
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Commit id: 384d1491ac0ebcb21e634d8274ab1974244270bd

adding aggregateBySample

Committed by: nosson
Author Name: nosson
Commit date: 2015-01-21 01:15:42 -0500
Author date: 2015-01-21 01:15:42 -0500


git-svn-id: file:///home/git/hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/metagenomeSeq@98545 bc3139a8-67e5-0310-9ffc-ced21a209358

Joseph Paulson authored on 21/01/2015 06:15:51
Showing 4 changed files
DESCRIPTION
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 Package: metagenomeSeq
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 Title: Statistical analysis for sparse high-throughput sequencing
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-Version: 1.9.17
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+Version: 1.9.18
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 Date: 2014-12-20
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 Author: Joseph Nathaniel Paulson, Hisham Talukder, Mihai Pop, Hector Corrada
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     Bravo
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@@ -33,5 +33,6 @@ Imports:
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     matrixStats,
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     gplots
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 VignetteBuilder: knitr
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-URL: http://cbcb.umd.edu/software/metagenomeSeq
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+URL: https://github.com/nosson/metagenomeSeq/
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+BugReports: https://github.com/nosson/metagenomeSeq/issues
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 biocViews: Classification, Clustering, GeneticVariability, DifferentialExpression, Microbiome, Metagenomics, Visualization, MultipleComparison, Sequencing, Software
NAMESPACE
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@@ -22,6 +22,8 @@ exportMethods(
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 export(
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 aggregateByTaxonomy,
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 aggTax,
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+aggregateBySample,
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+aggSamp,
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 biom2MRexperiment,
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 calculateEffectiveSamples,
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 calcNormFactors,
R/aggregateByTaxonomy.R
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@@ -76,3 +76,69 @@ aggregateByTaxonomy<-function(obj,lvl,alternate=FALSE,norm=FALSE,log=FALSE,aggfu
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 aggTax<-function(obj,lvl,alternate=FALSE,norm=FALSE,log=FALSE,aggfun = colSums,sl=1000,out='MRexperiment'){
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 	aggregateByTaxonomy(obj,lvl,alternate=alternate,norm=norm,log=log,aggfun = aggfun,sl=sl,out=out)
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 }
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+
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+#' @name aggregateBySample
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+#' @title Aggregates a MRexperiment object or counts matrix to by a factor.
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+#'
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+#' @details Using the phenoData information in the MRexperiment, calling aggregateBySample on a
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+#' MRexperiment and a particular phenoData column (i.e. 'diet') will aggregate counts
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+#' using the aggfun function (default rowMeans). Possible aggfun alternatives
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+#' include rowMeans and rowMedians.
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+#'
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+#' @param obj A MRexperiment object or count matrix.
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+#' @param fct phenoData column name from the MRexperiment object or if count matrix object a vector of labels.
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+#' @param aggfun Aggregation function.
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+#' @param out Either 'MRexperiment' or 'matrix'
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+#' @return An aggregated count matrix or MRexperiment object.
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+#' @aliases aggSamp
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+#' @rdname aggregateBySample
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+#' @export
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+#' @examples
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+#'
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+#' data(mouseData)
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+#' aggregateBySample(mouseData[1:100,],fct="diet",aggfun=rowSums)
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+#' # not run
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+#' # aggregateBySample(mouseData,fct="diet",aggfun=rowMedians)
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+#' # aggSamp(mouseData,fct='diet',aggfun=rowMaxs)
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+#'
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+aggregateBySample<-function(obj,fct,aggfun=rowMeans,out="MRexperiment"){
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+	if(class(obj)=="MRexperiment"){
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+		mat = MRcounts(obj)
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+		if(length(fct)==1) factors = as.character(pData(obj)[,fct])
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+		else factors = as.character(fct)
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+	} else {
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+		mat = obj
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+		factors = as.character(fct)
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+		if(length(factors)!=ncol(mat)) stop("If input is a count matrix, fct must be a vector of length = ncol(count matrix)")
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+	}
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+	if(!(out%in%c("MRexperiment","matrix"))){
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+		stop("The variable out must either be 'MRexperiment' or 'matrix'")
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+	}
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+	grps = split(seq_along(factors),factors)
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+
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+	newMat = array(NA,dim=c(nrow(obj),length(grps)))
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+	for(i in 1:length(grps)){
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+		newMat[,i] = aggfun(mat[,grps[[i]],drop=FALSE])
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+	}
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+	colnames(newMat) = names(grps)
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+	rownames(newMat) = rownames(obj)
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+	if(out=='matrix') return(newMat)
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+	if(out=='MRexperiment'){
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+		pd = data.frame(names(grps))
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+		colnames(pd) = "pd"
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+		rownames(pd) = names(grps)
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+		pd = as(pd,"AnnotatedDataFrame")
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+		if(class(obj)=="MRexperiment"){
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+			fd = as(fData(obj),"AnnotatedDataFrame")
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+			newObj = newMRexperiment(newMat,featureData=fd,phenoData=pd)
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+		} else {
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+			newObj = newMRexperiment(newMat,phenoData=pd)
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+		}
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+		return(newObj)
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+	}
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+}
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+#' @rdname aggregateBySample
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+#' @export
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+aggSamp<-function(obj,fct,aggfun=rowMeans,out='MRexperiment'){
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+	aggregateBySample(obj,fct,aggfun=aggfun,out=out)
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+}
man/aggregateBySample.Rd
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new file mode 100644
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+% Generated by roxygen2 (4.1.0): do not edit by hand
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+% Please edit documentation in R/aggregateByTaxonomy.R
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+\name{aggregateBySample}
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+\alias{aggSamp}
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+\alias{aggregateBySample}
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+\title{Aggregates a MRexperiment object or counts matrix to by a factor.}
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+\usage{
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+aggregateBySample(obj, fct, aggfun = rowMeans, out = "MRexperiment")
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+
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+aggSamp(obj, fct, aggfun = rowMeans, out = "MRexperiment")
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+}
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+\arguments{
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+\item{obj}{A MRexperiment object or count matrix.}
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+
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+\item{fct}{phenoData column name from the MRexperiment object or if count matrix object a vector of labels.}
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+
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+\item{aggfun}{Aggregation function.}
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+
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+\item{out}{Either 'MRexperiment' or 'matrix'}
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+}
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+\value{
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+An aggregated count matrix or MRexperiment object.
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+}
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+\description{
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+Aggregates a MRexperiment object or counts matrix to by a factor.
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+}
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+\details{
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+Using the phenoData information in the MRexperiment, calling aggregateBySample on a
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+MRexperiment and a particular phenoData column (i.e. 'diet') will aggregate counts
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+using the aggfun function (default rowMeans). Possible aggfun alternatives
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+include rowMeans and rowMedians.
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+}
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+\examples{
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+data(mouseData)
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+aggregateBySample(mouseData[1:100,],fct="diet",aggfun=rowSums)
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+# not run
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+# aggregateBySample(mouseData,fct="diet",aggfun=rowMedians)
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+# aggSamp(mouseData,fct='diet',aggfun=rowMaxs)
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+}
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+