IDEAS: individual level differential expression analysis for single-cell RNA-seq data

Genome Biology

Raphael Gottardo¹  Fang Han²  Zhen Miao²  Si Liu³  Mengqi Zhang³  Wei Sun³ 

[1] Biomedical Data Sciences Center, Lausanne University Hospital;Department of Statistics, University of Washington;Public Health Science Division, Fred Hutchison Cancer Research Center;

关键词: scRNA-seq;    IDEAS;    Differential expression;   

DOI  :  10.1186/s13059-022-02605-1

来源: DOAJ

【 摘 要 】

Abstract We consider an increasingly popular study design where single-cell RNA-seq data are collected from multiple individuals and the question of interest is to find genes that are differentially expressed between two groups of individuals. Towards this end, we propose a statistical method named IDEAS (individual level differential expression analysis for scRNA-seq). For each gene, IDEAS summarizes its expression in each individual by a distribution and then assesses whether these individual-specific distributions are different between two groups of individuals. We apply IDEAS to assess gene expression differences of autism patients versus controls and COVID-19 patients with mild versus severe symptoms.

【 授权许可】

Unknown