Learn R Programming

metacoder (version 0.3.7)

parse_phyloseq: Convert a phyloseq to taxmap

Description

Converts a phyloseq object to a taxmap object.

Usage

parse_phyloseq(obj, class_regex = "(.*)", class_key = "taxon_name")

Value

A taxmap object

Arguments

obj

A phyloseq object

class_regex

A regular expression used to parse data in the taxon names. There must be a capture group (a pair of parentheses) for each item in class_key. See parse_tax_data for examples of how this works.

class_key

(`character` of length 1) The identity of the capturing groups defined using `class_regex`. The length of `class_key` must be equal to the number of capturing groups specified in `class_regex`. Any names added to the terms will be used as column names in the output. At least one `"taxon_name"` must be specified. Only `"info"` can be used multiple times. Each term must be one of those described below: * `taxon_name`: The name of a taxon. Not necessarily unique, but are interpretable by a particular `database`. Requires an internet connection. * `taxon_rank`: The rank of the taxon. This will be used to add rank info into the output object that can be accessed by `out$taxon_ranks()`. * `info`: Arbitrary taxon info you want included in the output. Can be used more than once.

See Also

Other parsers: extract_tax_data(), lookup_tax_data(), parse_dada2(), parse_edge_list(), parse_greengenes(), parse_mothur_tax_summary(), parse_mothur_taxonomy(), parse_newick(), parse_phylo(), parse_qiime_biom(), parse_rdp(), parse_silva_fasta(), parse_tax_data(), parse_ubiome(), parse_unite_general()

Examples

Run this code
if (FALSE) {

# Install phyloseq to get example data
# source('http://bioconductor.org/biocLite.R')
# biocLite('phyloseq')

# Parse example dataset
library(phyloseq)
data(GlobalPatterns)
x <- parse_phyloseq(GlobalPatterns)

# Plot data
heat_tree(x,
          node_size = n_obs,
          node_color = n_obs,
          node_label = taxon_names,
          tree_label = taxon_names)

}


Run the code above in your browser using DataLab