pubmedtk

“Pubmed toolkit,” an R package that provides functions for downloading data via the Pubmed API and interpreting them.

Installing

You can install this package via CRAN with the following:

install.packages("pubmedtk")

Or if you want the most up to date version, you can do so via devtools:

install.packages("devtools")
library(devtools)
install_github("bgcarlisle/pubmedtk")
library(pubmedtk)

Pubmed API

You will need a Pubmed API key to access the Pubmed API. This is a 36-character code that is provided by Pubmed. If you don’t have one, you can generate one by following these instructions:

Go to Pubmed
Log in
Account > Account settings > API Key Management
Generate an API key
Save this in a plain-text file called api_key.txt in the root of your project and read this into your code using something like the following: ak <- readLines("api_key.txt")
Recommended: If you’re using git for version control, open the .gitignore file and add api_key.txt to the file, so that you don’t accidentally expose your Pubmed credentials to the world.

For all the examples below, assume that the api_key.txt file has already been written to disk.

Functions provided by `pubmedtk`

This package provides five functions: get_pmids_from_one_search(), get_pmids_from_searches(), get_metadata_from_one_pmid(), get_metadata_from_pmids(), and intersection_check().

`get_pmids_from_one_search()`

Returns a named list of PMID’s for a provided Pubmed search with 3 elements:

$pubmed_search_success, which is TRUE in the case that the provided query was searched successfully on Pubmed and FALSE otherwise.
$n_results, the number of results for the search as reported by Pubmed
$pmids, a list of PMID’s corresponding to the Pubmed search results for the query provided

Example:

## Read in API key
ak <- readLines("api_key.txt")

## Download PMID's for search query
result <- get_pmids_from_one_search("Carlisle B[Author]", ak)

## Extract first result
result$pmids[1]

`get_pmids_from_searches()`

This function downloads PMID results for a column of Pubmed search queries in a data frame and returns a data frame containing the original columns as well as three additional columns:

The pubmed_search_success column is TRUE in the case that the search rcesults were successfully obtained from Pubmed; FALSE in the case that an error occurred in search (e.g. due to a search query that is not well-formed).
The n_results column contains the number of research results for the query provided.
The pmids column returns a JSON-encoded list of PMID’s for the search query provided.

Note that only 10,000 PMID’s will be returned if your search has more than this number of results.

Example:

library(tidyverse)

## Read in API key
ak <- readLines("api_key.txt")

## Example Pubmed searches, some valid, some not, some with more than
## 10k results
searches <- tribble(
  ~terms,
  "Carlisle B[Author]",
  "NCT00267865",
  "(Clinical Trial[Publication Type]) AND ((\"2021/01/01\"[Date - Publication] : \"2022/12/31\"[Date - Publication]))",
  ""
)

## Download search results
results <- get_pmids_from_searches(searches, "terms", ak)

`get_metadata_from_one_pmid()`

Downloads metadata from the Pubmed API for a single PMID, and returns a named list of 8 elements:

$pubmed_dl_success, which is TRUE in the case that a corresponding Pubmed record was found and metadata downloaded and FALSE otherwise.
$doi, a character string containing the DOI for the publication with the PMID in question.
$languages, a list of languages corresponding to the publication with the PMID in question.
$pubtypes, a list of publication types corresponding to the publication with the PMID in question.
$pubdate, a string containing the publication date.
$epubdate, a string containing the e-publication date.
$authors, a list of authors of the publication with the PMID in question.
$abstract, a string containing the abstract for the publication.

Example:

## Read in API key
ak <- readLines("api_key.txt")

## Download Pubmed metadata
mdata <- get_metadata_from_one_pmid("29559429", ak)

## Extract first author
mdata$authors[1]

`get_metadata_from_pmids()`

Downloads metadata from Pubmed API for a column of PMID’s in a data frame, and returns a data frame containing the original columns as well as 8 additional columns:

The pubmed_dl_success column is TRUE in the case that metadata were successfully downloaded from Pubmed; FALSE in the case that an error occurred during downloading (e.g. due to a number that is well-formed but does not correspond to a true PMID); NA in the case that the supplied PMID is not well-formed (e.g. NA or non-numeric).
The doi column returns a DOI that corresponds to the PMID supplied if one is found, NA otherwise.
The languages column contains a JSON-encoded list of languages for the article in question.
The pubtypes column contains a JSON-encoded list of publication types for the article in question.
The pubdate column contains a string of the publication date.
The epubdate column contains a string of the e-publication date.
The authors column contains a JSON-encoded list of authors for the article in question.
The abstract column contains a string of the publication abstract (if it has been captured by Pubmed).

Example:

library(tidyverse)

## Read in API key
ak <- readLines("api_key.txt")

## Example publications and their corresponding PMID's (some valid and
## some not)
pubs <- tribble(
  ~pmid,
  "28837722",
  NA,
  "98472657638729",
  "borp",
  "29559429"
)

## Download Pubmed metadata
pm_meta <- get_metadata_from_pmids(pubs, "pmid", ak)

## Extract DOI's for those that were successfully downloaded
pm_meta |>
  filter(pubmed_dl_success) |>
  select(pmid, doi)

## A tibble: 2 × 2
##   pmid     doi                    
##   <chr>    <chr>                  
## 1 28837722 10.1001/jama.2017.11502
## 2 29559429 10.1136/bmj.k959

`intersection_check()`

This function takes a Pubmed search query and a set of PMID’s and indicates for each PMID whether it would or would not be contained in the results of the provided search query. The function returns the original data frame with the column of PMID’s to be checked, as well as two additional columns: pm_checked and found_in_pm_query.

The new pm_checked column is TRUE if Pubmed was successfully queried and NA if Pubmed was not checked for that PMID (this may occur in cases where the PMID to be checked is not well-formed).

The new found_in_pm_query column is TRUE if the PMID in question would appear in a search of Pubmed defined by the query provided; FALSE if it would not appear in such a search and NA if the PMID in question was not checked (this may occur in cases where the PMID is not well-formed).

Example:

library(tidyverse)

## Read in API key
ak <- readLines("api_key.txt")

## Example publications and their corresponding PMID's (some valid and
## some not)
pubs <- tribble(
  ~pmid,
  "29559429",
  "28837722",
  "28961465",
  "32278621",
  "one hundred of them",
  "28837722",
  "28961465"
)

## Check which PMID's are authored by someone named "Carlisle"
intersection_check(pubs, "pmid", "Carlisle[Author]", ak)

## # A tibble: 7 × 3
##   pmid                pm_checked found_in_pm_query
##   <chr>               <lgl>      <lgl>            
## 1 29559429            TRUE       TRUE             
## 2 28837722            TRUE       TRUE             
## 3 28961465            TRUE       FALSE            
## 4 32278621            TRUE       FALSE            
## 5 one hundred of them NA         NA               
## 6 28837722            TRUE       TRUE             
## 7 28961465            TRUE       FALSE

pubmedtk

Installing

Pubmed API

Functions provided by pubmedtk

get_pmids_from_one_search()

get_pmids_from_searches()

get_metadata_from_one_pmid()

get_metadata_from_pmids()

intersection_check()

Functions provided by `pubmedtk`

`get_pmids_from_one_search()`

`get_pmids_from_searches()`

`get_metadata_from_one_pmid()`

`get_metadata_from_pmids()`

`intersection_check()`