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An R package for metabarcoding research planning and analysis

Metacoder is an R package for reading, plotting, and manipulating large taxonomic data sets, like those generated from modern high-throughput sequencing, like metabarcoding (i.e. amplification metagenomics, 16S metagenomics, etc). It provides a tree-based visualization called "heat trees" used to depict statistics for every taxon in a taxonomy using color and size. It also provides various functions to do common tasks in microbiome bioinformatics on data in the taxmap format defined by the taxa package, such as:

  • Summing read counts/abundance per taxon
  • Converting counts to proportions and rarefaction of counts using vegan
  • Comparing the abundance (or other characteristics) of groups of samples (e.g., experimental treatments) per taxon
  • Combining data for groups of samples
  • Simulated PCR, via EMBOSS primersearch, for testing primer specificity and coverage of taxonomic groups
  • Converting common microbiome formats for data and reference databases into the objects defined by the taxa package.
  • Converting to and from the phyloseq format and the taxa format

Installation

This project is available on CRAN and can be installed like so:

install.packages("metacoder")

You can also install the development version for the newest features, bugs, and bug fixes:

install.packages("devtools")
devtools::install_github("grunwaldlab/metacoder")

Documentation

All the documentation for metacoder can be found on our website here:

https://grunwaldlab.github.io/metacoder_documentation/

Dependencies

The function that simulates PCR requires primersearch from the EMBOSS tool kit to be installed. This is not an R package, so it is not automatically installed. Type ?primersearch after installing and loading metacoder for installation instructions.

Relationship with other packages

Many of these operations can be done using other packages like phyloseq, which also provides tools for diversity analysis. The main strength of metacoder is that its functions use the flexible data types defined by taxa, which has powerful parsing and subsetting abilities that take into account the hierarchical relationship between taxa and user-defined data. In general, metacoder and taxa are more of an abstracted tool kit, whereas phyloseq has more specialized functions for community diversity data, but they both can do similar things. I encourage you to try both to see which fits your needs and style best. You can also combine the two in a single analysis by converting between the two data types when needed.

Citation

If you use metcoder in a publication, please cite our article in PLOS Computational Biology:

Foster ZSL, Sharpton TJ, Grünwald NJ (2017) Metacoder: An R package for visualization and manipulation of community taxonomic diversity data. PLOS Computational Biology 13(2): e1005404. https://doi.org/10.1371/journal.pcbi.1005404

Future development

Metacoder is under active development and many new features are planned. Some improvements that are being explored include:

  • Barcoding gap analysis and associated plotting functions
  • A function to aid in retrieving appropriate sequence data from NCBI for in silico PCR from whole genome sequences
  • Graphing of different node shapes in heat trees, possibly including pie graphs or PhyloPics.
  • Adding the ability to plot specific edge lengths in the heat trees so they can be used for phylogenetic trees.
  • Adding more data import and export functions to make parsing and writing common formats easier.

To see the details of what is being worked on, check out the issues tab of the Metacoder Github site.

License

This work is subject to the MIT License.

Acknowledgements

Metacoder's major dependencies are taxa, taxize, vegan, igraph, dplyr, and ggplot2.

This package includes code from the R package ggrepel to handle label overlap avoidance with permission from the author of ggrepel Kamil Slowikowski. We included the code instead of depending on ggrepel because we are using functions internal to ggrepel that might change in the future. We thank Kamil Slowikowski for letting us use his code and would like to acknowledge his implementation of the label overlap avoidance used in metacoder.

Feedback and contributions

We would like to hear about users' thoughts on the package and any errors they run into. Please report errors, questions or suggestions on the issues tab of the Metacoder Github site. We also welcome contributions via a Github pull request. You can also talk with us using our Google groups site.

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Version

Install

install.packages('metacoder')

Monthly Downloads

879

Version

0.3.2

License

GPL-2 | GPL-3

Maintainer

Zachary Foster

Last Published

April 8th, 2019

Functions in metacoder (0.3.2)

calc_obs_props

Calculate proportions from observation counts
calc_group_stat

Apply a function to groups of columns
calc_n_samples

Count the number of samples
calc_group_median

Calculate medians of groups of columns
calc_group_rsd

Relative standard deviations of groups of columns
calc_taxon_abund

Sum observation values for each taxon
can_be_num

Test if characters can be converted to numbers
everything

dplyr select_helpers
counts_to_presence

Apply a function to groups of columns
convert_base

Converts decimal numbers to other bases
fasta_headers

Get line numbers of FASTA headers
get_node_children

get_node_children
get_taxmap_other_cols

Parse the other_cols option
get_numeric_cols

Get numeric columns from taxmap table
filter_ambiguous_taxa

Filter ambiguous taxon names
get_taxonomy_levels

Get taxonomy levels
get_edge_parents

get_edge_parents
%>%

magrittr forward-pipe operator
get_taxmap_table

Get a table from a taxmap object
get_expected_data

Get a data set in as_phyloseq
make_dada2_asv_table

Make a imitation of the dada2 ASV abundance matrix
map_unique

Run a function on unique values of a iterable
matches

dplyr select_helpers
make_dada2_tax_table

Make a imitation of the dada2 taxonomy matrix
line_coords

Makes coordinates for a line
my_print

Print something
ncbi_sequence

Downloads sequences from ids
look_for_na

Look for NAs in parameters
parse_seq_input

Read sequences in an unknown format
ncbi_taxon_sample

Download representative sequences for a taxon
complement

Find complement of sequences
apply_color_scale

Covert numbers to colors
ambiguous_patterns

Get patterns for ambiguous taxa
.onAttach

Run when package loads
contains

dplyr select_helpers
parse_edge_list

Convert a table with an edge list to taxmap
parse_greengenes

Parse Greengenes release
parse_silva_fasta

Parse SILVA FASTA release
num_range

dplyr select_helpers
calc_group_mean

Calculate means of groups of columns
as_phyloseq

Convert taxmap to phyloseq
check_option_groups

Check option: groups
select_labels

Pick labels to show
split_by_level

Splits a taxonomy at a specific level or rank
edge_list_depth

Get distance from root of edgelist observations
write_mothur_taxonomy

Write an imitation of the Mothur taxonomy file
primersearch_raw

Use EMBOSS primersearch for in silico PCR
write_rdp

Write an imitation of the RDP FASTA database
get_taxmap_cols

Get a column subset
parse_newick

Parse a Newick file
compare_groups

Compare groups of samples
qualitative_palette

The default qualitative color palette
parse_phylo

Parse a phylo object
get_taxmap_data

Get a data set from a taxmap object
primersearch

Use EMBOSS primersearch for in silico PCR
hmp_otus

A HMP subset
rev_comp

Revere complement sequences
diverging_palette

The default diverging color palette
do_calc_on_num_cols

Run some function to produce new columns.
hmp_samples

Sample information for HMP subset
reverse

Reverse sequences
DNAbin_to_char

Converts DNAbin to a named character vector
primersearch_is_installed

Test if primersearch is installed
add_alpha

add_alpha
check_element_length

Check length of graph attributes
unique_mapping

get indexes of a unique set of the input
check_for_pkg

check for packages
get_numerics

Return numeric values in a character
read_fasta

Read a FASTA file
text_grob_length

Estimate text grob length
verify_color_range

Verify color range parameters
get_class_from_el

Get classification for taxa in edge list
inter_circle_gap

Finds the gap/overlap of circle coordinates
read_lines_apply

Apply a function to chunks of a file
get_optimal_range

Find optimal range
get_edge_children

get_edge_children
heat_tree

Plot a taxonomic tree
verify_size_range

Verify size range parameters
inverse

Generate the inverse of a function
parse_dada2

Convert the output of dada2 to a taxmap object
layout_functions

Layout functions
transform_data

Transformation functions
one_of

dplyr select_helpers
limited_print

Print a subset of a character vector
verify_taxmap

Check that an object is a taxmap
is_ambiguous

Find ambiguous taxon names
parse_qiime_biom

Parse a BIOM output from QIIME
zero_low_counts

Replace low counts with zero
heat_tree_matrix

Plot a matrix of heat trees
parse_rdp

Parse RDP FASTA release
parse_summary_seqs

Parse summary.seqs output
label_bounds

Bounding box coords for labels
make_fasta_with_u_replaced

Make a temporary file U's replaced with T
parse_ubiome

Converts the uBiome file format to taxmap
make_plot_legend

Make color/size legend
quantative_palette

The default quantative color palette
rarefy_obs

Calculate rarefied observation counts
metacoder

Metacoder
molten_dist

Get all distances between points
parse_mothur_tax_summary

Parse mothur *.tax.summary Classify.seqs output
verify_size

Verify size parameters
verify_label_count

Verify label count
parse_mothur_taxonomy

Parse mothur Classify.seqs *.taxonomy output
parse_phyloseq

Convert a phyloseq to taxmap
verify_trans

Verify transformation function parameters
write_greengenes

Write an imitation of the Greengenes database
parse_primersearch

Parse EMBOSS primersearch output
repo_url

Return github url
parse_unite_general

Parse UNITE general release FASTA
rescale

Rescale numeric vector to have specified minimum and maximum.
polygon_coords

Makes coordinates for a regular polygon
run_primersearch

Execute EMBOSS Primersearch
scale_bar_coords

Make scale bar division
write_silva_fasta

Write an imitation of the SILVA FASTA database
starts_with

dplyr select_helpers
startup_msg

Return startup message
write_unite_general

Write an imitation of the UNITE general FASTA database
calc_prop_samples

Calculate the proportion of samples
ends_with

dplyr select_helpers