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 aremedRxiv andbioRxiv, both of which are operated by the Cold Spring Harbor Laboratory.
The goal of themedrxivr R package is two-fold. In the first instance, it provides programmatic access to theCold 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 (seeData 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
To install the stable version of the package from CRAN:
install.packages("medrxivr")library(medrxivr)Alternatively, to install the development version from GitHub, use the following code:
install.packages("devtools")devtools::install_github("ropensci/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 endpointpreprint_data<-mx_api_content()mx_snapshot()provides access to a static snapshot of the medRxiv database. The snapshot is created each morning at 6am usingmx_api_content()and is stored as CSV file in themedrxivr-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 usingmx_crosscheck().
# Get a copy of the database from the daily snapshotpreprint_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 endpointpreprint_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) tomx_search() to search the preprint records using an advanced search strategy.
# Import the medrxiv databasepreprint_data<-mx_snapshot()# Perform a simple searchresults<-mx_search(data=preprint_data, query="dementia")#> Found 1045 record(s) matching your search.# Perform an advanced searchtopic1<-c("dementia","vascular","alzheimer's")# Combined with Boolean ORtopic2<-c("lipids","statins","cholesterol")# Combined with Boolean ORmyquery<-list(topic1,topic2)# Combined with Boolean ANDresults<-mx_search(data=preprint_data, query=myquery)#> Found 371 record(s) matching your search.You can also explore which search terms are contributing most to your search by settingreport = TRUE:
results<-mx_search(data=preprint_data, query=myquery, report=TRUE)#> Found 371 record(s) matching your search.#> Total topic 1 records: 5785#> dementia: 1045#> vascular: 4923#> alzheimer's: 1#> Total topic 2 records: 888#> lipids: 305#> statins: 124#> cholesterol: 580Further functionality
Export records identified by your search to a .BIB file
Pass the results of your search above (theresults object) to themx_export() to export references for preprints matching 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=results, file="mx_search_results.bib")Download PDFs for records returned by your search
Pass the results of your search above (theresults object) to themx_download() function to download a copy of the PDF for each record found by your search.
mx_download(results,# Object returned by mx_search(), above"pdf/",# Directory to save PDFs to create=TRUE)# Create the directory if it doesn't existAccessing the raw API data
By default, themx_api_*() functions clean the data returned by the API for use with othermedrxivr functions.
To access the raw data returned by the API, theclean argument should set toFALSE:
mx_api_content(to_date="2019-07-01", clean=FALSE)Seethis article for more details.
Detailed guidance
Detailed guidance, including advice on how to design complex search strategies, is available on themedrxivr website.
Linked repositories
See here for thecode used to take the daily snapshot andthe code that powers themedrxivr web app.
Other tools/packages for working with medRxiv/bioRxiv data
The focus ofmedrxivr is on providing tools to allow users to import and then search medRxiv and bioRxiv data. Below are a list of complementary packages that provide distinct but related functionality when working with medRxiv and bioRxiv data:
rbiorxivbyNicholas Fraser provides access to the same medRxiv and bioRxivcontent data asmedrxivr, but also provides access to theusage data (e.g. downloads per month) that the Cold Spring Harbour Laboratory API offers. This is useful if you wish to explore, for example,how the number of PDF downloads from bioRxiv has grown over time.
Code of conduct
Please note that this package is released with aContributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
