Skip to contents

This is an introduction to the helminthR package, whicih allows for the programmatic access to the London Natural History Museum’s helminth parasite database (available here). This database represents the largest known database of host-helminth interactions, containing host-helminth occurrence records for over 350 locations, including aquatic, marine, and terrestrial locations.

See software note in Ecography (available here)

Installation

From GitHub


# install.packages("devtools")
devtools::install_github("rOpenSci/helminthR")
library("helminthR")

From CRAN


install.packages("helminthR")

Package functionality

The package allows for the acquisition of host-helminth interaction records based on host name (genus or species), parasite name (genus, species, or group), and/or location (accepted region name as provided in data(locations). Parasite groups include “Acanthocephalans”, “Cestodes”, “Monogeans”, “Nematodes”, “Trematodes”, or “Turbs” (short for Turbellarians). The user can further define host species as occuring

  1. “In the wild”
  2. “Zoo captivity”
  3. “Domesticated”
  4. “Experimental”
  5. “Commercial source”
  6. “Accidental infestation”

by inputting the corresponding number above in the hostState argument.

The package itself has two base functions; loadData and cleanData

loadData()

This function loads the data. The data were previously served by the London Natural History Museum, so this package programmatically accessed them via API queries. The data have been archived, and this package ships with a zipped copy of the current release of the data.

data <- loadData()

cleanData()

There are numerous records that the end user may want to remove before analyzing the data. For instance, (Deer) is a valid host species listed, as is (duck). We can clean the data to remove these records and others not identified to species-level, as well as use taxize to access taxonomic data on hosts using the cleanData() function.

data2 <- cleanData(data)

data(locations)

A data file containing all the location names that can be queried, along with putative latitude and longitude coordinates for the centroid of each location can be found in data(locations). Note that this will replace any object in the global environment named locations. These names can be used to subset the existing data product (see loadData()). Below, I look at host-parasite associations recorded in France.


france <- data[which(data$country == 'France'), ]
dim(france)
head(france)

plotting host-helminth networks

Below, I provide an example of code for plotting the bipartite network of host-helminth interactions found in the state of Montana.


g <- igraph::graph_from_biadjacency_matrix(table(
  france$hostScientificName, 
  france$parasiteScientificName)
)
igraph::V(g)$name <- NA
igraph::E(g)$color <- 'black'

plot(g, 
    vertex.color=c("black","dodgerblue")[igraph::V(g)$type+1],
    vertex.size=5
)