gwasrapidd

'REST' 'API' Client for the 'NHGRI'-'EBI' 'GWAS' Catalog


Keywords
association-studies, gwas-catalog, human, r, rest-client, snp, trait, trait-ontology
License
MIT

Documentation

gwasrapidd

CRAN status R build status Codecov test coverage License: MIT

The goal of {gwasrapidd} is to provide programmatic access to the NHGRI-EBI Catalog of published genome-wide association studies.

Get started by reading the documentation.

Installation

Install {gwasrapidd} from CRAN:

install.packages("gwasrapidd")

You can instead install the development version of {gwasrapidd} by setting Ramiro Magno’s universe repository:

options(repos = c(ramiromagno = 'https://ramiromagno.r-universe.dev',
                CRAN = 'https://cloud.r-project.org'))

install.packages('gwasrapidd')

Cheatsheet

Example

Get studies related to triple-negative breast cancer:

library(gwasrapidd)
studies <- get_studies(efo_trait = 'triple-negative breast cancer')
studies@studies[1:4]
## # A tibble: 3 × 4
##   study_id     reported_trait                                    initi…¹ repli…²
##   <chr>        <chr>                                             <chr>   <chr>  
## 1 GCST002305   Breast cancer (estrogen-receptor negative, proge… 1,529 … 2,148 …
## 2 GCST010100   Breast cancer (estrogen-receptor negative, proge… 8,602 … <NA>   
## 3 GCST90029052 15-year breast cancer-specific survival (ER nega… 5,631 … <NA>   
## # … with abbreviated variable names ¹​initial_sample_size,
## #   ²​replication_sample_size

Find associated variants with study GCST002305:

variants <- get_variants(study_id = 'GCST002305')
variants@variants[c('variant_id', 'functional_class')]
## # A tibble: 5 × 2
##   variant_id functional_class   
##   <chr>      <chr>              
## 1 rs4245739  3_prime_UTR_variant
## 2 rs2363956  missense_variant   
## 3 rs10069690 intron_variant     
## 4 rs3757318  intron_variant     
## 5 rs10771399 intergenic_variant

Citing this work

{gwasrapidd} was published in Bioinformatics in 2019: https://doi.org/10.1093/bioinformatics/btz605.

To generate a citation for this publication from within R:

citation('gwasrapidd')
## 
## To cite gwasrapidd in publications use:
## 
##   Ramiro Magno, Ana-Teresa Maia, gwasrapidd: an R package to query,
##   download and wrangle GWAS Catalog data, Bioinformatics, btz605, 2
##   August 2019, Pages 1-2, https://doi.org/10.1093/bioinformatics/btz605
## 
## A BibTeX entry for LaTeX users is
## 
##   @Article{,
##     title = {gwasrapidd: an R package to query, download and wrangle GWAS Catalog data},
##     author = {Ramiro Magno and Ana-Teresa Maia},
##     journal = {Bioinformatics},
##     year = {2019},
##     pages = {1--2},
##     url = {https://doi.org/10.1093/bioinformatics/btz605},
##   }

Code of Conduct

Please note that the {gwasrapidd} project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

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Acknowledgements

This work would have not been possible without the precious help from the GWAS Catalog team, particularly Daniel Suveges.