Compare log2-frequency count of miRNA names between two topics

Compare log2-frequency count of miRNA names between two topics

compare_mir_count_log2(
  df,
  mir,
  topic = NULL,
  normalize = TRUE,
  col.topic = Topic,
  col.mir = miRNA,
  col.pmid = PMID,
  title = NULL
)

Arguments

df

Data frame containing miRNA names, topics, and PubMed-IDs.
mir

Character vector. Vector specifying which miRNA names to compare.
topic

Character vector. Optional. Vector specifying which topics to compare. If topic = NULL, all topics in df are used.
normalize

Boolean. If normalize = TRUE, proportion of abstracts mentioning a miRNA name compared to all abstracts of a topic are used. If normalize = FALSE, the absolute number of abstracts mentioning a miRNA name is used.
col.topic

Symbol. Column containing topics.
col.mir

Symbol. Column containing miRNA names.
col.pmid

Symbol. Column containing PubMed-IDs.
title

String. Plot title.

Value

List containing bar plot comparing the log2-frequency count of miRNA names between two topics and its corresponding data frame.

Details

Compare log2-frequency count of miRNA names between two topics by plotting the log2-ratio of the miRNA count in two topics. The miRNA count per topic can either be normalized, thus taking the proportion of abstracts mentioning a miRNA name compared to all abstracts in a topic, or not normalized, thus taking the absolute number of abstracts mentioning a miRNA in a topic. The log2-plot is greatly inspired by the book “tidytext: Text Mining and Analysis Using Tidy Data Principles in R.” by Silge and Robinson.

References

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.

See also

compare_mir_count(), compare_mir_count_unique()

Other compare functions: compare_mir_count_unique(), compare_mir_count(), compare_mir_terms_log2(), compare_mir_terms_scatter(), compare_mir_terms_unique(), compare_mir_terms()