The goal of smarterapi is to collect SMARTER data from SMARTER REST API and provide them to the user as a dataframe. Get more information with the online vignette.

The smarterapi package is only available from GitHub and can be installed as a source package or alternatively using the devtools package, for example:

# install devtools if needed
# install.packages("devtools")
devtools::install_github("cnr-ibba/r-smarter-api")

# Alternatively, you can use remotes (lighter dependency):
# install.packages("remotes")
remotes::install_github("cnr-ibba/r-smarter-api")

After the installation, you can load the package in your R session:

# import this library to deal with the SMARTER API
library(smarterapi)

NOTE: The smarterapi package is managed using renv: you don’t need to clone the entire repository to install the package. Managing the package installation with devtools lets you install the minimal set of dependencies needed to use the package. Cloning the repository is only needed if you want to contribute to the package development: in this case, please follow the instructions in the CONTRIBUTING.md guide to set up your development environment with all the required dependencies to build and test the package with vignettes.

After the public release of SMARTER data, there is no need to provide credentials to access the data. If you previously had credentials to access the data, you need to upgrade your installation of the smarterapi package.

smarterapi provides a set of functions to fetch data from SMARTER-backend endpoints described in the API documentation and return them as data.frame objects. For example, get_smarter_datasets() queries the Datasets endpoint, while get_smarter_samples() queries and parses the Samples endpoint response. Each smarterapi function is documented in R and you can get help on each function like any other R function. There are two types of parameters that can be used to fetch data from the SMARTER-backend: the species parameter, which can be Goat or Sheep for the Samples or Variants endpoints, and the query parameter which can be provided to any get_smarter_*() function. The species parameter is mandatory to query species-specific endpoints, while the query parameter is optional and needs to be specified as a list() object to filter your query to specific data. For example, if you need all foreground genotype datasets, you can collect data like this:

datasets <- get_smarter_datasets(
  query = list(type = "genotypes", type = "foreground")
)

If you require only background goat samples, you can do this:

goat_samples <- get_smarter_samples(
  species = "Goat", query = list(type = "background")
)

The full list of available options for each endpoint is documented in the SMARTER-backend Swagger documentation. The option names to use are the same as those described in the parameters section, and the descriptions and parameter types can give you hints on how to use the endpoints properly. For instance, parameters described as array of objects can be specified multiple times:

> goat_breeds <- get_smarter_breeds(query = list(species="Goat", search="land"))
> goat_breeds[c("name","code")]
            name code
1      Rangeland  RAN
2       Landrace  LNR
3         Landin  LND
4 Icelandic goat  ICL

> goat_samples <- get_smarter_samples(
    species = "Goat",
    query = list(
      breed_code="RAN",
      breed_code="LNR",
      breed_code="LND",
      breed_code="ICL"
    )
  )

This is a basic example showing how to collect data from the SMARTER REST API for Italian goats belonging to the Adaptmap dataset:

# Collect the dataset by providing part of the name with the search option.
# Since we are filtering for background genotypes only, only one dataset
# will be returned
datasets <- get_smarter_datasets(
  query = list(
    species = "Goat",
    search = "adaptmap",
    type = "genotypes",
    type = "background"
  )
)

# Get the dataset ID
adaptmap_id <- datasets["_id.$oid"][1]

# Collect all Italian goats from the Adaptmap dataset. Use the dataset ID
# to filter samples belonging to this dataset and the country option
# to filter for Italian samples only
adaptmap_goats <- get_smarter_samples(
  species = "Goat",
  query = list(
    dataset = adaptmap_id,
    country = "Italy"
  )
)

While this information can be retrieved through the SMARTER-backend, genotype data are available from the FTP site. The smarterapi package provides functions to easily download and manage these data:

get_smarter_genotypes(species = "Goat", assembly = "ARS1")

See the Collect genotypes vignette for more details and examples on how to extract genotype data from the samples of interest.

More examples are available in the vignettes, such as get started with smarterapi, how to collect data from the Variants endpoint or how to work with geographic coordinates.

To cite SMARTER data in publications, please use:

Cozzi P, Manunza A, Ramirez-Diaz J, Tsartsianidou V, Gkagkavouzis K, Peraza P, Johansson A, Arranz J, Freire F, Kusza S, Biscarini F, Peters L, Tosser-Klopp G, Ciappesoni G, Triantafyllidis A, Rupp R, Servin B, Stella A (2024). “SMARTER-database: a tool to integrate SNP array datasets for sheep and goat breeds.” GigaByte. doi:10.46471/gigabyte.139 https://doi.org/10.46471/gigabyte.139, https://github.com/cnr-ibba/SMARTER-database.

Or simply copy citation("smarterapi") output from your R console.

This package is licensed under GPL-3.0 License. See the LICENSE file for details.