R package AEenrich

Overview

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.

Install from CRAN

install.packages("AEenrich")

Then, load the package with

library(AEenrich)

Install from Github

If the devtools package is not yet installed, install it first:

install.packages('devtools')

Then run:

# install AEenrich from Github:
devtools::install_github('umich-biostatistics/AEenrich') 
library(AEenrich)

Example usage

For documentation pages:

?AEenrich
?enrich
?count_cases

Quick example:

# AEKS
## Type I data: data on report level
enrich(data = covid1, covar = c("SEX", "AGE"), p = 0, method = "aeks",
       n_perms = 1000, drug.case = "COVID19", dd.group = group_info,
       drug.control = "OTHER", min_size = 5, min_AE = 10, zero = FALSE)
## Type II data: aggregated data
enrich(data = covid2, covar = c("SEX", "AGE"), p = 0, method = "aeks",
       n_perms = 1000, drug.case = "DrugYes", dd.group = group_info,
       drug.control = "DrugNo", min_size = 5, min_AE = 10)
# AEFISHER
## Type I data: data on report level
enrich(data = covid1, covar = c("SEX", "AGE"), p = 0, method = "aefisher",
       n_perms = 1000, drug.case = "COVID19", dd.group = group_info,
       drug.control = "OTHER", min_size = 5, min_AE = 10, q.cut = 0.05, 
       or.cut = 1.5, cores = 8)
## Type II data: aggregated data
enrich(data = covid2, covar = c("SEX", "AGE"), p = 0, method = "aefisher",
       n_perms = 1000, drug.case = "DrugYes", dd.group = group_info,
       drug.control = "DrugNo", min_size = 5, min_AE = 10)

## Convert type I data to type II data
count_cases (data = covid1, drug.case = "COVID19", drug.control = "OTHER",
             covar_cont = c("AGE"), covar_disc = c("SEX"),
             breaks = list(c(16,30,50,65,120)))

Current Suggested Citation

1. Li, S. and Zhao, L. (2020). Adverse event enrichment tests using VAERS. arXiv:2007.02266.

2. Subramanian, A.e.a. (2005). Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. Proceedings of the National Academy of Sciences. 102. 15545-15550.

3. Tian, Lu & Greenberg, Steven & Kong, Sek Won & Altschuler, Josiah & Kohane, Isaac & Park, Peter. (2005). Discovering statistically significant pathways in expression profiling studies. Proceedings of the National Academy of Sciences of the United States of America. 102. 13544-9. 10.1073/pnas.0506577102.