Package: AEenrich 1.1.0

Michael Kleinsasser

AEenrich: Adverse Event Enrichment Tests

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) <arxiv:2007.02266>.

Authors:Shuoran Li [aut], Hongfan Chen [aut], Lili Zhao [aut], Michael Kleinsasser [aut, cre]

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# Install 'AEenrich' in R:
install.packages('AEenrich', repos = c('https://umich-biostatistics.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/umich-biostatistics/aeenrich/issues

Datasets:
  • covid1 - Covid Vaccine Adverse Event Data
  • covid2 - Covid Vaccine Adverse Event Data
  • group - Group Structure Data

On CRAN:

3.48 score 3 stars 1 scripts 280 downloads 2 exports 47 dependencies

Last updated 2 years agofrom:78580f863a. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-winNOTENov 15 2024
R-4.5-linuxNOTENov 15 2024
R-4.4-winNOTENov 15 2024
R-4.4-macNOTENov 15 2024
R-4.3-winNOTENov 15 2024
R-4.3-macNOTENov 15 2024

Exports:count_casesenrich

Dependencies:backportsbroomclicodetoolscolorspacecpp11doParalleldplyrfansifarverforeachgenericsggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmodelrmunsellnlmepillarpkgconfigplyrpurrrqvalueR6RColorBrewerRcppreshape2rlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr