Sccomp: Robust differential composition and variability analysis for single-cell data.

ABSTRACT: Cellular omics such as single-cell genomics, proteomics, and microbiomics allow the characterization of tissue and microbial community composition, which can be compared between conditions to identify biological drivers. This strategy has been critical to revealing markers of disease progression, such as cancer and pathogen infection. A dedicated statistical method for differential variability analysis is lacking for cellular omics data, and existing methods for differential composition analysis do not model some compositional data properties, suggesting there is room to improve model performance. Here, we introduce sccomp, a method for differential composition and variability analyses that jointly models data count distribution, compositionality, group-specific variability, and proportion

SUBMITTER: Mangiola S 

PROVIDER: S-EPMC10438834 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature