compare_mir_terms_scatter.Rd
Compare shared terms associated with a miRNA name over two topics.
compare_mir_terms_scatter( df, mir, top = 1000, token = "words", ..., topic = NULL, stopwords = stopwords_miretrieve, stopwords_ngram = TRUE, html = TRUE, colour.point = "red", colour.term = "black", col.mir = miRNA, col.abstract = Abstract, col.topic = Topic, col.pmid = PMID, title = NULL )
df | Data frame containing miRNA names, abstracts, topics, and PubMed-IDs. |
---|---|
mir | String. miRNA name of interest. |
top | Integer. Number of top terms to plot. |
token | String. Specifies how abstracts shall be split up. Taken from
|
... | Additional arguments for tokenization, if necessary. |
topic | Character vector. Optional. Specifies which topics to plot.
Must have length two.
If |
stopwords | Data frame containing stop words. |
stopwords_ngram | Boolean. Specifies if stop words shall be removed
from abstracts when using ngrams. Only applied when |
html | Boolean. Specifies if plot is returned as an HTML-widget or static. |
colour.point | String. Colour of points for scatter plot. |
colour.term | String. Colour of terms for scatter plot. |
col.mir | Symbol. Column containing miRNAs. |
col.abstract | Symbol. Column containing abstracts. |
col.topic | Symbol. Column containing topics names. |
col.pmid | Symbol. Column containing PubMed-IDs. |
title | String. Plot title. |
Scatter plot comparing shared terms of a miRNA between two topics.
Compare shared terms associated with a miRNA name over two topics. These terms are displayed
as a scatter plot, which is either interactive as an HTML-widget, or static. This
is regulated via the html
argument.
miRNA names and topics must be in a data frame df
, while terms are taken
from abstracts contained in df
.
Number of top terms to choose is regulated by top
. Terms are
evaluated as their raw count and plotted on a log10-scale.
compare_mir_terms_scatter()
is based on the tools available in the
tidytext package.
The term-plot is greatly inspired by
“tidytext: Text Mining and Analysis Using Tidy Data Principles in R.” by
Silge and Robinson.
Silge, Julia, and David Robinson. 2016. “tidytext: Text Mining and Analysis Using Tidy Data Principles in R.” JOSS 1 (3). The Open Journal. https://doi.org/10.21105/joss.00037.
compare_mir_terms()
, compare_mir_terms_log2()
Other compare functions:
compare_mir_count_log2()
,
compare_mir_count_unique()
,
compare_mir_count()
,
compare_mir_terms_log2()
,
compare_mir_terms_unique()
,
compare_mir_terms()