europepmc facilitates access to the Europe PMC RESTful Web Service. The client furthermore supports the Europe PMC Annotations API to retrieve text-mined concepts and terms per article.
Europe PMC covers life science literature and gives access to open access full texts. Europe PMC ingests all PubMed content and extends its index with other literature and patent sources.
For more infos on Europe PMC, see:
Levchenko, M., Gou, Y., Graef, F., Hamelers, A., Huang, Z., Ide-Smith, M., … McEntyre, J. (2017). Europe PMC in 2017. Nucleic Acids Research, 46(D1), D1254–D1260. https://doi.org/10.1093/nar/gkx1005
This client supports the following API methods from the Articles RESTful API:
| API-Method | Description | R functions |
|---|---|---|
| search | Search Europe PMC and get detailed metadata | epmc_search(), epmc_details(), epmc_search_by_doi() |
| profile | Obtain a summary of hit counts for several Europe PMC databases | epmc_profile() |
| citations | Load metadata representing citing articles for a given publication | epmc_citations() |
| references | Retrieve the reference section of a publication | epmc_refs() |
| databaseLinks | Get links to biological databases such as UniProt or ENA | epmc_db(), epmc_db_count() |
| labslinks | Access links to Europe PMC provided by third parties | epmc_lablinks(), epmc_lablinks_count() |
| fullTextXML | Fetch full-texts deposited in PMC | epmc_ftxt() |
| bookXML | retrieve book XML formatted full text for the Open Access subset of the Europe PMC bookshelf | epmc_ftxt_book() |
From the Europe PMC Annotations API:
| API-Method | Description | R functions |
|---|---|---|
| annotationsByArticleIds | Get the annotations contained in the list of articles specified | epmc_annotations_by_id() |
From CRAN
The latest development version can be installed using the remotes package:
Loading into R
The search covers both metadata (e.g. abstracts or title) and full texts. To build your query, please refer to the comprehensive guidance on how to search Europe PMC: https://europepmc.org/help. Provide your query in the Europe PMC search syntax to epmc_search().
europepmc::epmc_search(query = '"2019-nCoV" OR "2019nCoV"')
#> # A tibble: 100 × 29
#> id source pmid doi title authorString journalTitle issue journalVolume
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 33406042 MED 33406042 10.1… 2019… Xiao M, Liu… IEEE/ACM Tr… 4 18
#> 2 34059225 MED 34059225 10.1… Livi… Santillan-G… Med Intensi… 5 45
#> 3 34181072 MED 34181072 10.1… Self… Varghese JJ… Support Car… <NA> <NA>
#> 4 34108756 MED 34108756 10.2… COVI… Gabarron E,… Bull World … 6 99
#> 5 33197230 MED 33197230 10.2… Sear… Lazarus JV,… J Med Inter… 11 22
#> 6 33181701 MED 33181701 10.1… The … Kim YJ, Qia… Medicine (B… 46 99
#> 7 34291001 MED 34291001 10.4… How … Moradi G, G… Med J Islam… <NA> 35
#> 8 33521188 MED 33521188 10.1… Tota… Chen AZ, Sh… Arthroplast… <NA> 8
#> 9 33009914 MED 33009914 10.1… A da… Zhu Z, Meng… Database (O… <NA> 2020
#> 10 32341597 MED 32341597 10.1… Obes… Carretero G… Rev Clin Es… 6 220
#> # … with 90 more rows, and 20 more variables: pubYear <chr>, journalIssn <chr>,
#> # pageInfo <chr>, pubType <chr>, isOpenAccess <chr>, inEPMC <chr>,
#> # inPMC <chr>, hasPDF <chr>, hasBook <chr>, hasSuppl <chr>,
#> # citedByCount <int>, hasReferences <chr>, hasTextMinedTerms <chr>,
#> # hasDbCrossReferences <chr>, hasLabsLinks <chr>,
#> # hasTMAccessionNumbers <chr>, firstIndexDate <chr>,
#> # firstPublicationDate <chr>, pmcid <chr>, versionNumber <int>Be aware that Europe PMC expands queries with MeSH synonyms by default. You can turn this behavior off using the synonym = FALSE parameter.
By default, epmc_search() returns 100 records. To adjust the limit, simply use the limit parameter.
See vignette Introducing europepmc, an R interface to Europe PMC RESTful API for a long-form documentation about how to search Europe PMC with this client.
epmc_hits_trend()There is also a nice function allowing you to easily create review graphs like described in Maëlle Salmon’s blog post:
tt_oa <- europepmc::epmc_hits_trend("Malaria", period = 1995:2019, synonym = FALSE)
tt_oa
#> # A tibble: 25 × 3
#> year all_hits query_hits
#> <int> <dbl> <dbl>
#> 1 1995 449064 1495
#> 2 1996 458526 1572
#> 3 1997 456744 1873
#> 4 1998 474613 1762
#> 5 1999 493745 1947
#> 6 2000 532019 2092
#> 7 2001 545674 2187
#> 8 2002 561425 2378
#> 9 2003 588572 2612
#> 10 2004 628141 2845
#> # … with 15 more rows
# we use ggplot2 for plotting the graph
library(ggplot2)
ggplot(tt_oa, aes(year, query_hits / all_hits)) +
geom_point() +
geom_line() +
xlab("Year published") +
ylab("Proportion of articles on Malaria in Europe PMC")
For more info, read the vignette about creating literature review graphs:
https://docs.ropensci.org/europepmc/articles/evergreenreviewgraphs.html
Check out the tidypmc package
https://github.com/ropensci/tidypmc
The package maintainer, Chris Stubben (@cstubben), has also created an Shiny App that allows you to search and browse Europe PMC:
https://github.com/cstubben/euPMC
oai to get metadata and full text via Europe PMC’s OAI interface: https://github.com/ropensci/oairentrez to interact with NCBI databases such as PubMed: https://github.com/ropensci/rentrezfulltext package gives access to supplementary material of open access life-science publications in Europe PMC: https://github.com/ropensci/fulltextPlease note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
License: GPL-3
Please use the issue tracker for bug reporting and feature requests.
