Pseudobulk with proper offsets has the same statistical properties as generalized linear mixed models in single-cell case-control studies.

ABSTRACT:

Motivation

Generalized linear mixed models (GLMMs), such as the negative-binomial or Poisson linear mixed model, are widely applied to single-cell RNA sequencing data to compare transcript expression between different conditions determined at the subject level. However, the model is computationally intensive, and its relative statistical performance to pseudobulk approaches is poorly understood.

Results

We propose offset-pseudobulk as a lightweight alternative to GLMMs. We prove that a count-based pseudobulk equipped with a proper offset variable has the same statistical properties as GLMMs in terms of both point estimates and standard errors. We confirm our findings using simulations based on real data. Offset-pseudobulk is substantially faster (>x10) and numerically more s

SUBMITTER: Lee H 

PROVIDER: S-EPMC11343365 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature