AEenrich-package

The count_cases function converts report-level data into aggregated data by
grouping on specified covariates. Use <code>count_cases</code> to summarize adverse
event reports into analysis-ready tables. See the GitHub home page at
<a href="https://github.com/umich-biostatistics/AEenrich">https://github.com/umich-biostatistics/AEenrich</a> or run <code>?count_cases</code>
for examples.
Perform adverse event enrichment tests. The <code>enrich</code> function implements
enrichment analysis for adverse event count data, which contain many zeros and
ties. Two methods are provided: <code>AEFisher</code>, a modified Fisher’s exact test
based on pre-selected significant adverse events, and <code>AEKS</code>, a modified
Kolmogorov–Smirnov statistic. See the GitHub home page at
<a href="https://github.com/umich-biostatistics/AEenrich">https://github.com/umich-biostatistics/AEenrich</a> or run <code>?enrich</code> for
examples.

We extend existing gene enrichment tests to perform adverse
event enrichment analysis. Unlike the continuous gene expression data,
adverse event data are counts. Therefore, adverse event data has many zeros
and ties. We propose two enrichment tests. One is a modified Fisher's exact
test based on pre-selected significant adverse events, while the other is
based on a modified Kolmogorov-Smirnov statistic. We add Covariate
adjustment to improve the analysis."Adverse event enrichment tests using
VAERS" Shuoran Li, Lili Zhao (2020) <doi:10.48550/arXiv.2007.02266>.

Michael Kleinsasser

AEenrich

Adverse Event Enrichment Tests

Shuoran Li

Hongfan Chen

Lili Zhao

AEenrich-package function

Maintainer: Michael Kleinsasser <a href="/link/mkleinsa%40umich.edu?package=AEenrich&version=1.1.1" data-mini-rdoc="AEenrich::mkleinsa@umich.edu">mkleinsa@umich.edu</a>
Authors:<ul>
<li>Shuoran Li <a href="/link/shuoranl%40umich.edu?package=AEenrich&version=1.1.1" data-mini-rdoc="AEenrich::shuoranl@umich.edu">shuoranl@umich.edu</a></li>
<li>Hongfan Chen <a href="/link/chenhf%40umich.edu?package=AEenrich&version=1.1.1" data-mini-rdoc="AEenrich::chenhf@umich.edu">chenhf@umich.edu</a></li>
<li>Lili Zhao <a href="/link/zhaolili%40med.umich.edu?package=AEenrich&version=1.1.1" data-mini-rdoc="AEenrich::zhaolili@med.umich.edu">zhaolili@med.umich.edu</a></li>
</ul>

Author

The count_cases function converts report-level data into aggregated data by
grouping on specified covariates. Use <code>count_cases</code> to summarize adverse
event reports into analysis-ready tables. See the GitHub home page at
<a href='https://github.com/umich-biostatistics/AEenrich'>https://github.com/umich-biostatistics/AEenrich</a> or run <code>?count_cases</code>
for examples.
Perform adverse event enrichment tests. The <code>enrich</code> function implements
enrichment analysis for adverse event count data, which contain many zeros and
ties. Two methods are provided: <code>AEFisher</code>, a modified Fisher’s exact test
based on pre-selected significant adverse events, and <code>AEKS</code>, a modified
Kolmogorov–Smirnov statistic. See the GitHub home page at
<a href='https://github.com/umich-biostatistics/AEenrich'>https://github.com/umich-biostatistics/AEenrich</a> or run <code>?enrich</code> for
examples.

AEenrich: Adverse Event Enrichment Tests — AEenrich-package

Maintainer: Michael Kleinsasser <a href='mailto:mkleinsa@umich.edu'>mkleinsa@umich.edu</a>
Authors:<ul>
<li>Shuoran Li <a href='mailto:shuoranl@umich.edu'>shuoranl@umich.edu</a></li>
<li>Hongfan Chen <a href='mailto:chenhf@umich.edu'>chenhf@umich.edu</a></li>
<li>Lili Zhao <a href='mailto:zhaolili@med.umich.edu'>zhaolili@med.umich.edu</a></li>
</ul>

AEenrich-package: AEenrich: Adverse Event Enrichment Tests

Description

Arguments

Author

See Also