Dozer: Debiased personalized gene co-expression networks for population-scale scRNA-seq data.

ABSTRACT: Population-scale single cell RNA-seq (scRNA-seq) datasets create unique opportunities for quantifying expression variation across individuals at the gene co-expression network level. Estimation of co-expression networks is well-established for bulk RNA-seq; however, single-cell measurements pose novel challenges due to technical limitations and noise levels of this technology. Gene-gene correlation estimates from scRNA-seq tend to be severely biased towards zero for genes with low and sparse expression. Here, we present Dozer to debias gene-gene correlation estimates from scRNA-seq datasets and accurately quantify network level variation across individuals. Dozer corrects correlation estimates in the general Poisson measurement model and provides a metric to quantify genes measured with hi

SUBMITTER: Lu S 

PROVIDER: S-EPMC10168282 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature