rplos tutorial

The rplos package interacts with the API services of PLoS (Public Library of Science) Journals. In order to use rplos, you need to obtain your own key to their API services. Instruction for obtaining and installing keys so they load automatically when you launch R are on our GitHub Wiki page Installation and use of API keys.

This tutorial will go through three use cases to demonstrate the kinds of things possible in rplos.

Search across PLoS papers in various sections of papers
Search for terms and visualize results as a histogram OR as a plot through time
Text mining of scientific literature

Load package from CRAN

install.packages("rplos")

library(rplos)

Search across PLoS papers in various sections of papers

searchplos is a general search, and in this case searches for the term Helianthus and returns the DOI's of matching papers

searchplos(terms = "Helianthus", fields = "id", limit = 5)

                            id
1 10.1371/journal.pone.0057533
2 10.1371/journal.pone.0045899
3 10.1371/journal.pone.0037191
4 10.1371/journal.pone.0051360
5 10.1371/journal.pone.0070347

Get only full article DOIs

searchplos(terms = "*:*", fields = "id", toquery = "doc_type:full", start = 0, 
    limit = 20)

                             id
1  10.1371/journal.pgen.1001387
2  10.1371/journal.pone.0058892
3  10.1371/journal.pone.0015116
4  10.1371/journal.pgen.1001385
5  10.1371/journal.pone.0015114
6  10.1371/journal.pone.0030759
7  10.1371/journal.pone.0015112
8  10.1371/journal.pone.0030758
9  10.1371/journal.pone.0015111
10 10.1371/journal.pone.0058887
11 10.1371/journal.pone.0024514
12 10.1371/journal.pone.0030762
13 10.1371/journal.pone.0071223
14 10.1371/journal.pone.0030761
15 10.1371/journal.pone.0024513
16 10.1371/journal.pone.0024512
17 10.1371/journal.pone.0058890
18 10.1371/journal.pone.0030760
19 10.1371/journal.pgen.1001384
20 10.1371/journal.pone.0024511

Get DOIs for only PLoS One articles

searchplos(terms = "*:*", fields = "id", toquery = "cross_published_journal_key:PLoSONE", 
    start = 0, limit = 15)

                                                    id
1                    10.1371/journal.pone.0071225/body
2            10.1371/journal.pone.0071225/introduction
3  10.1371/journal.pone.0071225/results_and_discussion
4   10.1371/journal.pone.0071225/materials_and_methods
5  10.1371/journal.pone.0071225/supporting_information
6                         10.1371/journal.pone.0058892
7                   10.1371/journal.pone.0058892/title
8                10.1371/journal.pone.0058892/abstract
9              10.1371/journal.pone.0058892/references
10                   10.1371/journal.pone.0058892/body
11           10.1371/journal.pone.0058892/introduction
12 10.1371/journal.pone.0058892/results_and_discussion
13  10.1371/journal.pone.0058892/materials_and_methods
14                        10.1371/journal.pone.0015116
15                  10.1371/journal.pone.0015116/title

Get DOIs for full article in PLoS One

searchplos(terms = "*:*", fields = "id", toquery = list("cross_published_journal_key:PLoSONE", 
    "doc_type:full"), start = 0, limit = 20)

                             id
1  10.1371/journal.pone.0058892
2  10.1371/journal.pone.0015116
3  10.1371/journal.pone.0015114
4  10.1371/journal.pone.0030759
5  10.1371/journal.pone.0015112
6  10.1371/journal.pone.0030758
7  10.1371/journal.pone.0015111
8  10.1371/journal.pone.0058887
9  10.1371/journal.pone.0024514
10 10.1371/journal.pone.0030762
11 10.1371/journal.pone.0071223
12 10.1371/journal.pone.0030761
13 10.1371/journal.pone.0024513
14 10.1371/journal.pone.0024512
15 10.1371/journal.pone.0058890
16 10.1371/journal.pone.0030760
17 10.1371/journal.pone.0024511
18 10.1371/journal.pone.0021422
19 10.1371/journal.pone.0062009
20 10.1371/journal.pone.0030767

Serch for many terms

terms <- c("ecology", "evolution", "science")
lapply(terms, function(x) searchplos(x, limit = 2))

[[1]]
                            id
1 10.1371/journal.pone.0059813
2 10.1371/journal.pone.0001248

[[2]]
                            id
1 10.1371/journal.pbio.0050030
2 10.1371/journal.pbio.0030245

[[3]]
                            id
1 10.1371/journal.pbio.0020122
2 10.1371/journal.pbio.1001166

Search on specific sections

A suite of functions were created as light wrappers around searchplos as a shorthand to search specific sections of a paper.

plosauthor searchers in authors
plosabstract searches in abstracts
plostitle searches in titles
plosfigtabcaps searches in figure and table captions
plossubject searches in subject areas

plosauthor searches across authors, and in this case returns the authors of the matching papers. the fields parameter determines what is returned

plosauthor(terms = "Eisen", fields = "author", limit = 10)

                                           author
1                                Jonathan A Eisen
2                                Jonathan A Eisen
3                   Garmay Leung, Michael B Eisen
4                 Richard W Lusk, Michael B Eisen
5  Leonid Teytelman, Michael B Eisen, Jasper Rine
6                 Richard W Lusk, Michael B Eisen
7                 Lars Eisen, Saul Lozano-Fuentes
8          Jonathan A Eisen, Catriona J MacCallum
9   Martin Wu, Sourav Chatterji, Jonathan A Eisen
10                 Peter A Combs, Michael B Eisen

plosabstract searches across abstracts, and in this case returns the id and title of the matching papers

plosabstract(terms = "drosophila", fields = "id,title", limit = 5)

                            id
1 10.1371/journal.pbio.0040198
2 10.1371/journal.pbio.0030246
3 10.1371/journal.pone.0012421
4 10.1371/journal.pbio.0030389
5 10.1371/journal.pbio.1000342
                                                                      title
1                                                               All for All
2                               School Students as Drosophila Experimenters
3                      Host Range and Specificity of the Drosophila C Virus
4               New Environments Set the Stage for Changing Tastes in Mates
5 Variable Transcription Factor Binding: A Mechanism of Evolutionary Change

plostitle searches across titles, and in this case returns the title and journal of the matching papers

plostitle(terms = "drosophila", fields = "title,journal", limit = 10)

                      journal
1                PLoS Biology
2                PLoS Biology
3                    PLoS ONE
4  PLoS Computational Biology
5                PLoS Biology
6               PLoS Genetics
7                PLoS Biology
8                PLoS Biology
9                    PLoS ONE
10                   PLoS ONE
                                                   title
1            School Students as Drosophila Experimenters
2          Identification of Drosophila MicroRNA Targets
3               A Tripartite Synapse Model in Drosophila
4             Parametric Alignment of Drosophila Genomes
5            Expression in Aneuploid Drosophila S2 Cells
6  Phenotypic Plasticity of the Drosophila Transcriptome
7       Reinforcement of Gametic Isolation in Drosophila
8            Combinatorial Coding for Drosophila Neurons
9                              A DNA Virus of Drosophila
10           Quantification of Food Intake in Drosophila

Search for terms and visualize results as a histogram OR as a plot through time

plosword allows you to search for 1 to K words and visualize the results as a histogram, comparing number of matching papers for each word

out <- plosword(list("monkey", "Helianthus", "sunflower", "protein", "whale"), 
    vis = "TRUE")
out$table

  No_Articles       Term
1        6154     monkey
2         196 Helianthus
3         509  sunflower
4       64832    protein
5         702      whale

out$plot

plot of chunk plosword

You can also pass in curl options, in this case get verbose information on the curl call.

plosword("Helianthus", callopts = list(verbose = TRUE))

Number of articles with search term 
                                196

Visualize terms

plot_througtime allows you to search for up to 2 words and visualize the results as a line plot through time, comparing number of articles matching through time. Visualize with the ggplot2 package, only up to two terms for now.

plot_throughtime(terms = "phylogeny", limit = 200, gvis = FALSE)

plot of chunk throughtime1

plot_throughtime(list("drosophila", "monkey"), 100)

plot of chunk throughtime2

OR using google visualizations through the googleVis package, check it your self using, e.g.

plot_throughtime(terms = list("drosophila", "flower"), limit = 200, gvis = TRUE)

…And a google visualization will render on your local browser and you can play with three types of plots (point, histogram, line), all through time. The plot is not shown here, but try it out for yourself!!