Accessing NCBI data with the Rentrez package

R Community of Practice June 15 - July 20

Irmarie Fraticelli-Rodriguez

7/13/23

Learning Goals:

Our goals for today are:

Become familiar Rentrez.
Learn basic search functions.
Extract information from the esumaries.

The Data

Scenario:

Today our data comes from PubMed, a National Center for Biotechnology Information (NCBI) database. Our data outputs, will contain bibliographic information about our search query.

Challenges of Working with Data from an Unknown Source

The data may not arranged in a standardized format (BIBFRAME, MARC, METS, MODS, EAD…)
The source documentation may be incomplete, or may not answer our questions.
Not knowing what extra steps we may need to take to clean the data, so it can be usable.

We want to accomplish the following tasks:

Download Rentrez.
Perform simple and boolean searches.
Create a graph using your search results.

What is Rentrez?

Rentrez is an R interface that allows its users to interact with NCBI API.

With Rentrez, you do not need to use any additional program or terminal to access NCBI Data.

This means that you can request data from multiple databases (PubMed, SNP, Clinvar, SRA, Gene, and others) in the same RStudio Session.

Install and Load `Rentrez`

Now, remember that you need to install any new package that you want to use in RStudio. Also, once you have the package you need to load it.

#install.packages('rentrez')
library(rentrez)

Rentrez Functions

The functions listed below help you learn a little bit more about Rentrez and NCBI Databases.

Function	Usage
entrez_dbs()	List of Entrez Databases
entrez_db_summary()	Brief description of what the database is
entrez_db_searchable()	Set of search fields that can used with this database

Performing searches with Rentrez

The functions listed below help you perform searches to a NCBI Database.

Function	Usage
entrez_search()	Allows you to perform simple or boolean searches
entrez_summary()	Allows you to retrieve basic information about the records found
extract_from_esummary()	Extract elements from a list of esummary records

entrez_search()

Similar to PubMed, Rentrez allows you to perform simple or boolean searches using the same structure that you would use in the PubMed search bar. The allowed boolean terms are AND, OR, and NOT.

First, let’s learn the syntax for a simple and a boolean search:

Simple Search:

pcos_pm <- entrez_search(db="pubmed", term = "pcos[all]")

Boolean search:

pcos_ir_pm <- entrez_search(db="pubmed", term= "pcos[all] AND insulin resistance[all]")

entrez_summary()

Now let’s retrieve basic information about the records we collected in one of our searches. But, first, let’s learn the syntax of the entrez_summary() function.

summary_pcos_pm <- entrez_summary(db="pubmed", id=pcos_pm$ids)

extract_from_esummary()

This function helps you navigate through an XMLInternalDocument and extract elements from a list of esummary records. But, first, let’s learn the syntax of the extract_from_esummary() function.

uids <- extract_from_esummary(summary_pcos_pm,"uid")
authors <- extract_from_esummary(summary_pcos_pm,"authors")["name",]
pubdate <- extract_from_esummary(summary_pcos_pm,"pubdate")

Exercise: Let’s practice!

Now lets perform our own searches!

We are going to use the Rentrez functions to extract data from an NCBI database.

Our objective is to:

Build your query: Identify your search terms, adequate database, search fields and perform the search using rentrez.
Get article/object summaries.
Select the values that you would like to save (for example author, title, source).
Create a graph that represents the results of your search.

STEP #1

Build your query: Identify your search terms, adequate database, and search fields and perform the search using Rentrez.

# Im interested in seeing Dr. Kristen Stafford Publications

search <- entrez_search(db="pubmed", term = "Kristen A. Stafford[AUTH]",retmax=100)
search

Entrez search result with 51 hits (object contains 51 IDs and no web_history object)
 Search term (as translated):  stafford, kristen a[Author]

STEP #2

Get article summaries

summary <- entrez_summary(db="pubmed", id=search$ids)
summary

List of  51 esummary records. First record:

 $`37247622`
esummary result with 42 items:
 [1] uid               pubdate           epubdate          source           
 [5] authors           lastauthor        title             sorttitle        
 [9] volume            issue             pages             lang             
[13] nlmuniqueid       issn              essn              pubtype          
[17] recordstatus      pubstatus         articleids        history          
[21] references        attributes        pmcrefcount       fulljournalname  
[25] elocationid       doctype           srccontriblist    booktitle        
[29] medium            edition           publisherlocation publishername    
[33] srcdate           reportnumber      availablefromurl  locationlabel    
[37] doccontriblist    docdate           bookname          chapter          
[41] sortpubdate       sortfirstauthor

STEP #3

Select the values that you would like to save (for example author, title, source)

# I want to know how many publications she has and in what journal she publishes the most. 

library(tidyverse)

pubdate <- extract_from_esummary(summary,"pubdate") %>%
  substr(start= 1, stop=4)
source <- extract_from_esummary(summary,"source")

STEP #4

Create a graph that represents the results of your search.

ggplot(mapping = aes(x=source)) + 
  geom_bar() +
  theme(axis.text.x = element_text(angle = 90)) + # To rotate journals names
  labs(title = "Kristen's Stafford Publications per journal", # Set up graph title and labels
       x="Journal", y= "Amount")

ggplot(mapping = aes(x=pubdate)) +
  geom_bar() +
  theme(axis.text.x = element_text(angle = 90)) +
   labs(title = "Kristen's Stafford Publications per year", # Set up graph title and labels
       x="Year", y= "Amount")