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An increasingly important source of health-related bibliographic content are preprints - preliminary versions of research articles that have yet to undergo peer review. The two preprint repositories most relevant to health-related sciences are medRxiv and bioRxiv, both of which are operated by the Cold Spring Harbor Laboratory.

The goal of the medrxivr R package is two-fold. In the first instance, it provides programmatic access to the Cold Spring Harbour Laboratory (CSHL) API, allowing users to easily download medRxiv and bioRxiv preprint metadata (e.g. title, abstract, publication date, author list, etc) into R. The package also provides access to a maintained static snapshot of the medRxiv repository (see Data sources). Secondly, medrxivr provides functions to search the downloaded preprint records using regular expressions and Boolean logic, as well as helper functions that allow users to export their search results to a .BIB file for easy import to a reference manager and to download the full-text PDFs of preprints matching their search criteria.

Installation

You can install the stable version of this package using:

install.packages("medrxivr")
library(medrxivr)

Data sources

medRxiv data

medrixvr provides two ways to access medRxiv data:

  • mx_api_content(server = "medrxiv") creates a local copy of all data available from the medRxiv API at the time the function is run.
# Get a copy of the database from the live medRxiv API endpoint
preprint_data <- mx_api_content()  
  • mx_snapshot() provides access to a static snapshot of the medRxiv database. The snapshot is created each morning at 6am using mx_api_content() and is stored as CSV file in the medrxivr-data repository. This method does not rely on the API (which can become unavailable during peak usage times) and is usually faster (as it reads data from a CSV rather than having to re-extract it from the API). Discrepancies between the most recent static snapshot and the live database can be assessed using mx_crosscheck().
# Get a copy of the database from the daily snapshot
preprint_data <- mx_snapshot()  

The relationship between the two methods for the medRxiv database is summarised in the figure below:

bioRxiv data

Only one data source exists for the bioRxiv repository:

  • mx_api_content(server = "biorxiv") creates a local copy of all data available from the bioRxiv API endpoint at the time the function is run. Note: due to it’s size, downloading a complete copy of the bioRxiv repository in this manner takes a long time (~ 1 hour).
# Get a copy of the database from the live bioRxiv API endpoint
preprint_data <- mx_api_content(server = "biorxiv")

Dataset description

The dataset (in this case, results) returned by the search function above contains 14 variables:

Variable Description
ID Unique identifier
title Preprint title
abstract Preprint abstract
authors Author list in the format ‘LastName, InitalOfFirstName.’ (e.g. McGuinness, L.). Authors are seperated by a semi-colon.
date Date the preprint was posted, in the format YYYYMMDD.
category On submission, medRxiv asks authors to classify their preprint into one of a set number of subject categories.
doi Preprint Digital Object Identifier.
version Preprint version number. As authors can update their preprint at any time, this indicates which version of a given preprint the record refers to.
author_corresponding Corresponding authors name.
author_corresponding_institution Corresponding author’s institution.
link_page Link to preprint webpage. The “?versioned=TRUE” is required, as otherwise, the URL will resolve to the most recent version of the article (assuming there is >1 version available).
link_pdf Link to preprint PDF. This is used by mx_download() to download a copy of the PDF for that preprint.
license Preprint license
published If the preprint was subsequently published in a peer-reviewed journal, this variable contains the DOI of the published version.

Export records identified by your search to a .BIB file

medrxivr provides a helper function to export your search results to a .BIB file so that they can be easily imported into a reference manager (e.g. Zotero, Mendeley)


mx_export(data = mx_results,
          file = tempfile(fileext = ".bib"))

Further guidance

Please see the medrxivr website vignette for extended guidance on developing search strategies and for detailed instructions on interacting with the Cold Springs Harbour API for medRxiv and bioRxiv.