nebula-package: Negative Binomial Mixed Models Using Large-Sample...

In nebula: Negative Binomial Mixed Models Using Large-Sample Approximation for Differential Expression Analysis of ScRNA-Seq Data

Negative Binomial Mixed Models Using Large-Sample Approximation for Differential Expression Analysis of ScRNA-Seq Data

Description

A fast negative binomial mixed model for conducting association analysis of multi-subject single-cell data. It can be used for identifying marker genes, differential expression and co-expression analyses. The model includes subject-level random effects to account for the hierarchical structure in multi-subject single-cell data. See He et al. (2021) <doi:10.1038/s42003-021-02146-6>.

Details

nebula is an R package for performing association analysis using a fast negative binomial mixed model for multi-subject single-cell data.

Author(s)

Liang He [aut, cre], Raghav Sharma [ctb]

Maintainer: Liang He <[e-mail]>

References

He, L., Davila-Velderrain, J., Sumida, T. S., Hafler, D. A., Kellis, M., & Kulminski, A. M. (2021). NEBULA is a fast negative binomial mixed model for differential or co-expression analysis of large-scale multi-subject single-cell data. Communications biology, 4(1), 1-17.

Examples

library(nebula)
data(sample_data)
pred = model.matrix(~X1+X2+cc,data=sample_data$pred)
re = nebula(count=sample_data$count,id=sample_data$sid,pred=pred)

nebula documentation built on May 29, 2024, 8:56 a.m.