Awesome
rmangal :package: - an R Client for the Mangal database <img src="man/figures/logo.png" width="130" align="right"/>
Context
Mangal -- a global ecological interactions database -- serializes ecological interaction matrices into nodes (e.g. taxon, individuals or population) and interactions (i.e. edges). For each network, Mangal offers the opportunity to store study context such as the location, sampling environment, inventory date and informations pertaining to the original publication. For every nodes involved in the ecological networks, Mangal references unique taxonomic identifiers such as Encyclopedia of Life (EOL), Catalogue of Life (COL), Global Biodiversity Information Facility (GBIF) etc. and can extend nodes informations to individual traits.
rmangal is an R client to the Mangal database and provides various functions
to explore his content through search functions. It offers methods to retrieve
networks structured as mgNetwork
or mgNetworksCollection
S3 objects and
methods to convert mgNetwork
to other class objects in order to analyze and
visualize networks properties: igraph
,
tidygraph
, and
ggraph
.
Installation
So far, only the development version is available and can be installed via the remotes :package:
R> remotes::install_github("ropensci/rmangal")
R> library("rmangal")
How to use rmangal
There are seven search_*()
functions to explore the content of Mangal, for
instance search_datasets()
:
R> mgs <- search_datasets("lagoon")
Found 2 datasets
Once this first step achieved, networks found can be retrieved with the get_collection()
function.
R> mgn <- get_collection(mgs)
get_collection()
returns an object mgNetwork
if there is one network
returned, otherwise an object mgNetworkCollection
, which is a list of
mgNetwork
objects.
R> class(mgn)
[1] "mgNetworksCollection"
R> mgn
A collection of 3 networks
* Network # from data set #
* Description: Dietary matrix of the Huizache–Caimanero lagoon
* Includes 189 edges and 26 nodes
* Current taxonomic IDs coverage for nodes of this network:
--> ITIS: 81%, BOLD: 81%, EOL: 85%, COL: 81%, GBIF: 0%, NCBI: 85%
* Published in ref # DOI:10.1016/s0272-7714(02)00410-9
* Network # from data set #
* Description: Food web of the Brackish lagoon
* Includes 27 edges and 11 nodes
* Current taxonomic IDs coverage for nodes of this network:
--> ITIS: 45%, BOLD: 45%, EOL: 45%, COL: 45%, GBIF: 18%, NCBI: 45%
* Published in ref # DOI:NA
* Network # from data set #
* Description: Food web of the Costal lagoon
* Includes 34 edges and 13 nodes
* Current taxonomic IDs coverage for nodes of this network:
--> ITIS: 54%, BOLD: 54%, EOL: 54%, COL: 54%, GBIF: 15%, NCBI: 54%
* Published in ref # DOI:NA
igraph
and
tidygraph
offer powerful features to
analyze networks and rmangal provides functions to convert mgNetwork
to
igraph
and tbl_graph
so that the user can easily benefit from those
packages.
R> ig <- as.igraph(mgn[[1]])
R> class(ig)
[1] "igraph"
R> library(tidygraph)
R> tg <- as_tbl_graph(mgn[[1]])
R> class(tg)
[1] "tbl_graph" "igraph"
:book: Note that the vignette "Get started with rmangal" will guide the reader through several examples and provide further details about rmangal features.
How to publish ecological networks
We are working on that part. The networks publication process will be facilitated with structured objects and tests suite to maintain data integrity and quality.Comments and suggestions are welcome, feel free to open issues.
rmangal
vs rglobi
Those interested only in pairwise interactions among taxons may consider using
rglobi
, an R package that provides an interface to the GloBi
infrastructure. GloBi
provides open access to aggregated interactions from heterogeneous sources. In
contrast, Mangal gives access to the original networks and open the gate to
study ecological networks properties (i.e. connectance, degree etc.) along large
environmental gradients, which wasn't possible using the GloBi infrastructure.
Older versions
- See https://github.com/mangal-interactions/rmangal-v1 for the first version of the client.
- Note that due to changes in the RESTful API, there is no backward compatibility.
Acknowledgment
We are grateful to Noam Ross for acting as an editor during the review process. We also thank Anna Willoughby and Thomas Lin Petersen for reviewing the package. Their comments strongly contributed to improve the quality of rmangal.
Code of conduct
Please note that the rmangal
project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Meta
- Get citation information for
rmangal
in R doingcitation(package = 'rmangal')
- Please report any issues or bugs.