affiliation

library(badger)

r badge_devel("hugofitipaldi/affiliation", "blue") r badge_lifecycle("experimental", "orange") r badge_last_commit("hugofitipaldi/affiliation")

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

Installation

Development version of the package can be installed from Github with:

install.packages("remotes")
remotes::install_github("hugofitipaldi/affiliation")

Usage

Country of affiliation

affiliation::get_affiliations(PMID = "30237159")

Function for non-indexed publications

For publications in PubMed with lack of affiliation information, such as for publications prior to 2014 (when PubMed only included the first author affiliation among the accessible metadata information), the extraction of country of affiliation can be done by the auth_aff_dict() function.

This function was built based on the structure in which author-affiliation information is presented at PubMed Central (PMC):

The same dictionary-like structure is also extensively used in the PDF formats of publications, thus, one can simply copy and paste this information and use it as parameters for the the function:

authors_names <- "Peter M. Visscher,1,2 Matthew A. Brown,1 Mark I. McCarthy,3,4 Jian Yang,5"

affiliation_dict <- "1 University of Queensland Diamantina Institute, Princess Alexandra Hospital, Brisbane, Queensland 4102, Australia
2 The Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
3 Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
4 Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital Old Road, Headington Oxford OX3 7LJ, UK
5 Queensland Institute of Medical Research, 300 Herston Road, Brisbane, Queensland 4006, Australia"

affiliation::auth_aff_dict(authors_names, affiliation_dict)

If you use this package in you research, please cite:

Hugo Fitipaldi, Paul W Franks, Ethnic, gender and other sociodemographic biases in genome-wide association studies for the most burdensome non-communicable diseases: 2005–2022, Human Molecular Genetics, 2022;, ddac245, https://doi.org/10.1093/hmg/ddac245



hugofitipaldi/affiliation documentation built on May 12, 2024, 9:30 a.m.