Get started

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

When the package is available from CRAN, install the stable version with:

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

The canonical CRAN package page is https://CRAN.R-project.org/package=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 package reads a manifest from the snapshot release assets for this repository, downloads the referenced compressed CSV files, and caches them locally. This method does not rely on the live API during ordinary use and is usually faster than re-extracting records from the API. The function prints the latest record date included in the snapshot; 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 static 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")

Performing your search

Once you have created a local copy of either the medRxiv or bioRxiv preprint database, you can pass this object (preprint_data in the examples above) to mx_search() to search the preprint records using an advanced search strategy.


# Perform a simple search
results <- mx_search(data = preprint_data,
                     query ="dementia")

# Perform an advanced search
topic1  <- c("dementia","vascular","alzheimer's")  # Combined with Boolean OR
topic2  <- c("lipids","statins","cholesterol")     # Combined with Boolean OR
myquery <- list(topic1, topic2)                    # Combined with Boolean AND

results <- mx_search(data = preprint_data,
                     query = myquery)

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"))

Download PDFs for records identified by your search

Pass the results of your search above (results) to the mx_download() function to download a copy of the PDF for each record.


mx_download(results,        # Object returned by mx_search
            tempdir(),      # Temporary directory to save PDFs to 
            create = TRUE)  # Create the directory if it doesn't exist

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.

Yaoxiang Li

2026-05-11