phyloseq: mt-methods – R documentation

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mt-methods

Multiple testing of taxa abundance according to sample categories/classes

Description

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.

Usage

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", ...)

Arguments

`physeq`	(Required). `otu_table-class` or `phyloseq-class`. In this multiple testing framework, different taxa correspond to variables (hypotheses), and samples to observations.
`classlabel`	(Required). A single character index of the sample-variable in the `sample_data` of `physeq` that will be used for multiple testing. Alternatively, `classlabel` can be a custom integer (or numeric coercable to an integer), character, or factor with length equal to `nsamples(physeq)`. NOTE: the default test applied to each taxa is a two-sample two-sided `t.test`, WHICH WILL FAIL with an error if you provide a data variable (or custom vector) that contains MORE THAN TWO classes. One alternative to consider is an F-test, by specifying `test="f"` as an additional argument. See the first example below, and/or further documentation of `mt.maxT` or `mt.minP` for other options and formal details.
`minPmaxT`	(Optional). Character string. `"mt.minP"` or `"mt.maxT"`. Default is to use `"mt.minP"`.
`method`	(Optional). Additional multiple-hypthesis correction methods. A character vector from the set `p.adjust.methods`. Default is `"fdr"`, for the Benjamini and Hochberg (1995) method to control False Discovery Rate (FDR). This argument is passed on to `p.adjust`, please see that documentation for more details.
`...`	(Optional). Additional arguments, forwarded to `mt.maxT` or `mt.minP`

Value

A dataframe with components specified in the documentation for mt.maxT or mt.minP, respectively.

Examples

## # 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="fdr", 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)

phyloseq

Handling and analysis of high-throughput microbiome census data

v1.34.0

AGPL-3

Authors

Paul J. McMurdie <joey711@gmail.com>, Susan Holmes <susan@stat.stanford.edu>, with contributions from Gregory Jordan and Scott Chamberlain

Initial release

2019-04-23