| mt {phyloseq} | R Documentation |
Please note that it is up to you to perform any necessary
normalizing / standardizing transformations prior to these tests.
See for instance transform_sample_counts.
mt(physeq, classlabel, minPmaxT = "minP", method = "fdr", ...) ## S4 method for signature 'phyloseq,ANY' mt(physeq, classlabel, minPmaxT = "minP", method = "fdr", ...) ## S4 method for signature 'otu_table,integer' mt(physeq, classlabel, minPmaxT = "minP", method = "fdr", ...) ## S4 method for signature 'otu_table,numeric' mt(physeq, classlabel, minPmaxT = "minP", method = "fdr", ...) ## S4 method for signature 'otu_table,logical' mt(physeq, classlabel, minPmaxT = "minP", method = "fdr", ...) ## S4 method for signature 'otu_table,character' mt(physeq, classlabel, minPmaxT = "minP", method = "fdr", ...) ## S4 method for signature 'otu_table,factor' mt(physeq, classlabel, minPmaxT = "minP", method = "fdr", ...)
physeq |
(Required). |
classlabel |
(Required). A single character index of the sample-variable
in the NOTE: the default test applied to each taxa is a two-sample two-sided
|
minPmaxT |
(Optional). Character string. |
method |
(Optional). Additional multiple-hypthesis correction methods.
A character vector from the set |
... |
(Optional). Additional arguments, forwarded to
|
A dataframe with components specified in the documentation for
mt.maxT or mt.minP, respectively.
## # Simple example, testing genera that sig correlate with Enterotypes
data(enterotype)
# Filter samples that don't have Enterotype
x <- subset_samples(enterotype, !is.na(Enterotype))
# (the taxa are at the genera level in this dataset)
res = mt(x, "Enterotype", method=c("fdr", "bonferroni"), test="f", B=300)
head(res, 10)
## # Not surprisingly, Prevotella and Bacteroides top the list.
## # Different test, multiple-adjusted t-test, whether samples are ent-2 or not.
## mt(x, get_variable(x, "Enterotype")==2)