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

In metagenomeSeq: Statistical analysis for sparse high-throughput sequencing

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,
  featureOrder = NULL,
  returnFullHierarchy = TRUE,
  out = "MRexperiment"
)

aggTax(
  obj,
  lvl,
  alternate = FALSE,
  norm = FALSE,
  log = FALSE,
  aggfun = colSums,
  sl = 1000,
  featureOrder = NULL,
  returnFullHierarchy = TRUE,
  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.
featureOrder	Hierarchy of levels in taxonomy as fData colnames
returnFullHierarchy	Boolean value to indicate return single column of fData or all columns of hierarchy
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)

metagenomeSeq documentation built on Nov. 8, 2020, 5:34 p.m.