perm_test_abc

This function assesses the significance of ABC model results through randomization.
It generates a null distribution by permuting the co-occurrence matrix.

A suite of tools for literature-based discovery in biomedical research.
Provides functions for retrieving scientific articles from 'PubMed' and
other NCBI databases, extracting biomedical entities (diseases, drugs, genes, etc.),
building co-occurrence networks, and applying various discovery models
including 'ABC', 'AnC', 'LSI', and 'BITOLA'. The package also includes
visualization tools for exploring discovered connections.

Chao Liu Liu

LBDiscover

Literature-Based Discovery Tools for Biomedical Research

Chao Liu 

perm_test_abc function

<dl><dt>abc_results</dt>
<dd>A data frame containing ABC results.</dd>
<dt>co_matrix</dt>
<dd>The co-occurrence matrix used to generate the ABC results.</dd>
<dt>n_permutations</dt>
<dd>Number of permutations to perform.</dd>
<dt>alpha</dt>
<dd>Significance level.</dd></dl>

Arguments

Perform randomization test for ABC model — perm_test_abc

<dl>

<dt>abc_results</dt>
<dd>A data frame containing ABC results.</dd>


<dt>co_matrix</dt>
<dd>The co-occurrence matrix used to generate the ABC results.</dd>


<dt>n_permutations</dt>
<dd>Number of permutations to perform.</dd>


<dt>alpha</dt>
<dd>Significance level.</dd>

</dl>

perm_test_abc: Perform randomization test for ABC model

Description

Usage

Value

Arguments