tip_glom, but uses categorical data
instead of a tree. In principal, other categorical data known for all taxa
could also be used in place of taxonomy,
but for the moment, this must be stored in the taxonomyTable
of the data. Also, columns/ranks to the right of the rank chosen to use
for agglomeration will be replaced with NA,
because they should be meaningless following agglomeration.tax_glom(physeq, taxrank=rank_names(physeq)[1], NArm=TRUE, bad_empty=c(NA, "", " ", "\t"))phyloseq-class or otu_table.rank_names(physeq).
The default value is rank_names(physeq)[1],
which may agglomerate too broadly for a given experiment.
You are strongly encouraged to try different values for this argument.TRUE.
CAUTION. The decision to prune (or not) taxa for which you lack categorical
data could have a large effect on downstream analysis. You may want to
re-compute your analysis under both conditions, or at least think carefully
about what the effect might be and the reasons explaining the absence of
information for certain taxa. In the case of taxonomy, it is often a result
of imprecision in taxonomic designation based on short phylogenetic sequences
and a patchy system of nomenclature. If this seems to be an issue for your
analysis, think about also trying the nomenclature-agnostic tip_glom
method if you have a phylogenetic tree available.c(NA, "", " ", "\t").
Defines the bad/empty values
that should be ignored and/or considered unknown. They will be removed
from the internal agglomeration vector derived from the argument to tax,
and therefore agglomeration will not combine taxa according to the presence
of these values in tax. Furthermore, the corresponding taxa can be
optionally pruned from the output if NArm is set to TRUE.physeq.tip_glom# data(GlobalPatterns) # ## print the available taxonomic ranks # colnames(tax_table(GlobalPatterns)) # ## agglomerate at the Family taxonomic rank # (x1 <- tax_glom(GlobalPatterns, taxrank="Family") ) # ## How many taxa before/after agglomeration? # ntaxa(GlobalPatterns); ntaxa(x1) # ## Look at enterotype dataset... # data(enterotype) # ## print the available taxonomic ranks. Shows only 1 rank available, not useful for tax_glom # colnames(tax_table(enterotype))