miRetrieve (version 1.3.4)

plot_score_animals: Plot frequency of animal model scores in abstracts

Description

Plot frequency of animal model scores in abstracts.

Usage

plot_score_animals(
  df,
  keywords = animal_keywords,
  case = FALSE,
  bins = NULL,
  colour = "steelblue3",
  col.abstract = Abstract,
  col.pmid = PMID,
  title = NULL
)

Arguments

df

Data frame containing abstracts.

keywords

Character vector. Vector containing keywords. The animal model score is calculated based on these keywords. How much weight a keyword in keywords carries is determined how often it is present in keywords, e.g. if a keyword is mentioned twice in keywords and it is mentioned only once in an abstract, it adds 2 points to the score.

case

Boolean. If case = TRUE, terms contained in keywords are case sensitive. If case = FALSE, terms contained in keywords are case insensitive.

bins

Integer. Specifies how many bins are used to plot the distribution. If bins = NULL, bins are calculated over the whole range of scores, with one bin per score.

colour

String. Colour of histogram.

col.abstract

Symbol. Column containing abstracts.

col.pmid

Symbol. Column containing PubMed-IDs.

title

String. Plot title.

Value

Histogram displaying the distribution of animal scores in abstracts.

Details

Plots a frequency distribution of animal model scores in abstracts of a data frame. The animal model score is influenced by the choice of terms in keywords. Plotting the distribution can help deciding if the terms are well-chosen, or in choosing the right threshold to decide which abstracts are considered to contain animal models.

See Also

calculate_score_animals()

Other score functions: assign_topic(), calculate_score_animals(), calculate_score_biomarker(), calculate_score_patients(), calculate_score_topic(), plot_score_biomarker(), plot_score_patients(), plot_score_topic()