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ARS Home » Pacific West Area » Corvallis, Oregon » Horticultural Crops Research Unit » Research » Publications at this Location » Publication #336198
Title: Metacoder: An R package for visualization and manipulation of community taxonomic diversity data

Author
item FOSTER, ZACHARY - Oregon State University
item SHARPTON, THOMAS - Oregon State University
item Grunwald, Niklaus - Nik

Submitted to: PLoS Computational Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/10/2017
Publication Date: 2/21/2017
Citation: Foster, Z.S., Sharpton, T.J., Grunwald, N.J. 2017. Metacoder: An R package for visualization and manipulation of community taxonomic diversity data. PLoS Computational Biology. 13(2):e1005404. doi:10.1371/journal.pcbi.1005404.

Interpretive Summary: Data on the number of species found in an ecological community are often graphed as stacked bar charts or pie graphs. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. We developed the software package metacoder for easily creating and plotting hierarchical data. Metacoder has been designed for data from metabarcoding research, but can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual.

Technical Abstract: Community composition data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. As an alternative, we developed metacoder, an R package for easily parsing, manipulating, and plotting hierarchical data. Metacoder includes a dynamic and flexible function that can parse most text-based formats that contain either taxonomic classifications, taxon names, taxon identifiers, or sequence identifiers. Metacoder can then subset, sample, and order this parsed data using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function enables quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to tree node and edge color and size. Metacoder also allows exploration of barcode primer bias by integrating functions to run digital PCR. Metacoder has been designed for data from metabarcoding research, but can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual.