ccdf is a package for performing single-cell RNA-seq differential
expression analysis and more generally complex hypothesis testing.
The main function of the package is ccdf_testing(). It allows to use
either an asymptotic test for large sample size or a permutation test
for small sample size with the argument method.
The methods implemented in this package are detailed in the following article:
Gauthier M, Agniel D, Thiébaut R & Hejblum BP (2020). Distribution-free complex hypothesis testing for single-cell RNA-seq differential expression analysis, BioRxiv doi:10.1101/2021.05.21.445165
ccdf is available from CRAN.
install.packages("ccdf")To install ccdf, you can download the development version on
GitHub.
#install.packages("devtools")
devtools::install_github("Mgauth/ccdf")Here is a basic example which shows how to use ccdf with simple
generated data.
## Data Generation
X <- data.frame("X1" = as.factor(rbinom(n=100, size = 1, prob = 0.5)))
Y <- data.frame("gene1" = t(replicate(10, ((X$X1==1)*rnorm(n = 50,0,1)) + ((X$X1==0)*rnorm(n = 50,0.5,1)))))# Hypothesis testing
res_asymp <- ccdf_testing(exprmat=Y, variable2test=X, test="asymptotic") # asymptotic test
res_perm <- ccdf_testing(exprmat=Y, variable2test=X, test="permutations",
adaptive=TRUE) # adaptive permutation test– Marine Gauthier, Denis Agniel, Rodolphe Thiébaut & Boris Hejblum