metagenomeSeq (version 1.14.0)

aggregateByTaxonomy: Aggregates a MRexperiment object or counts matrix to a particular level.

Description

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 = FALSE, log = FALSE, aggfun = colSums, sl = 1000, out = "MRexperiment")
aggTax(obj, lvl, alternate = FALSE, norm = FALSE, log = FALSE, aggfun = colSums, sl = 1000, out = "MRexperiment")

Arguments

obj

A MRexperiment object or count matrix.

lvl

featureData column name from the MRexperiment object or if count matrix object a vector of labels.

alternate

Use the rowname for undefined OTUs instead of aggregating to "no_match".

norm

Whether to aggregate normalized counts or not.

log

Whether or not to log2 transform the counts - if MRexperiment object.

aggfun

Aggregation function.

sl

scaling value, default is 1000.

out

Either 'MRexperiment' or 'matrix'

Value

An aggregated count matrix.

Examples

data(mouseData)
aggregateByTaxonomy(mouseData[1:100,],lvl="class",norm=TRUE,aggfun=colSums)
# not run
# aggregateByTaxonomy(mouseData,lvl="class",norm=TRUE,aggfun=colMedians)
# aggTax(mouseData,lvl='phylum',norm=FALSE,aggfun=colSums)