Theoretical framework for the difference of two negative binomial distributions and its application in comparative analysis of sequencing data.

ABSTRACT: High-throughput sequencing (HTS) technologies have been instrumental in investigating biological questions at the bulk and single-cell levels. Comparative analysis of two HTS data sets often relies on testing the statistical significance for the difference of two negative binomial distributions (DOTNB). Although negative binomial distributions are well studied, the theoretical results for DOTNB remain largely unexplored. Here, we derive basic analytical results for DOTNB and examine its asymptotic properties. As a state-of-the-art application of DOTNB, we introduce DEGage, a computational method for detecting differentially expressed genes (DEGs) in scRNA-seq data. DEGage calculates the mean of the sample-wise differences of gene expression levels as the test statistic and determines signi

SUBMITTER: Petrany A 

PROVIDER: S-EPMC11529838 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature