Metacoder is an R package for parsing, 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
metacoder package, such as:
phyloseqformat and the
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
metacoder, which has powerful parsing and subsetting abilities that take into account the hierarchical relationship between taxa and user-defined data. In general,
metacoder is 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 using the
This project is available on CRAN and can be installed like so:
You can also install the development version for the newest features, bugs, and bug fixes:
The function that simulates PCR requires
primersearch from the EMBOSS (Rice, Longden, and Bleasby 2000) 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.
Metacoder is under active development and many new features are planned. Some improvements that are being explored include:
Metacoder’s major dependencies are
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 or the comments section below.
Rice, Peter, Ian Longden, and Alan Bleasby. 2000. “EMBOSS: The European Molecular Biology Open Software Suite.” Elsevier Current Trends.