aggregateByTaxonomy {metagenomeSeq} | R Documentation |
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.
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" )
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' |
An aggregated count matrix.
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)