IDEAS: individual level differential expression analysis for single-cell RNA-seq data.
Genome Biol
; 23(1): 33, 2022 01 24.
Article
in English
| MEDLINE | ID: covidwho-1649470
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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Autistic Disorder
/
Software
/
Sequence Analysis, RNA
/
Single-Cell Analysis
/
COVID-19
Type of study:
Experimental Studies
/
Observational study
/
Prognostic study
/
Randomized controlled trials
Limits:
Humans
Language:
English
Journal:
Genome Biol
Journal subject:
Molecular Biology
/
Genetics
Year:
2022
Document Type:
Article
Affiliation country:
S13059-022-02605-1
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