phyloseq: merge_samples-methods – R documentation

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merge_samples-methods

Merge samples based on a sample variable or factor.

Description

The purpose of this method is to merge/agglomerate the sample indices of a phyloseq object according to a categorical variable contained in a sample_data or a provided factor.

Usage

merge_samples(x, group, fun=mean)

## S4 method for signature 'sample_data'
merge_samples(x, group, fun = mean)

## S4 method for signature 'otu_table'
merge_samples(x, group)

## S4 method for signature 'phyloseq'
merge_samples(x, group, fun = mean)

Arguments

`x`	(Required). An instance of a phyloseq class that has sample indices. This includes `sample_data-class`, `otu_table-class`, and `phyloseq-class`.
`group`	(Required). Either the a single character string matching a variable name in the corresponding sample_data of `x`, or a factor with the same length as the number of samples in `x`.
`fun`	(Optional). The function that will be used to merge the values that correspond to the same group for each variable. It must take a numeric vector as first argument and return a single value. Default is `mean`. Note that this is (currently) ignored for the otu_table, where the equivalent function is `sum`, but evaluated via `rowsum` for efficiency.

Details

NOTE: (phylo) trees and taxonomyTable-class are not modified by this function, but returned in the output object as-is.

Value

A phyloseq object that has had its sample indices merged according to the factor indicated by the group argument. The output class matches x.

Examples

#
data(GlobalPatterns)
GP = GlobalPatterns
mergedGP = merge_samples(GlobalPatterns, "SampleType")
SD = merge_samples(sample_data(GlobalPatterns), "SampleType")
print(SD)
print(mergedGP)
sample_names(GlobalPatterns)
sample_names(mergedGP)
identical(SD, sample_data(mergedGP))
# The OTU abundances of merged samples are summed
# Let's investigate this ourselves looking at just the top10 most abundance OTUs...
OTUnames10 = names(sort(taxa_sums(GP), TRUE)[1:10])
GP10  = prune_taxa(OTUnames10,  GP)
mGP10 = prune_taxa(OTUnames10, mergedGP)
ocean_samples = sample_names(subset(sample_data(GP), SampleType=="Ocean"))
print(ocean_samples)
otu_table(GP10)[, ocean_samples]
rowSums(otu_table(GP10)[, ocean_samples])
otu_table(mGP10)["Ocean", ]

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