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IDEAS: individual level differential expression analysis for single-cell RNA-seq data
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IDEAS: individual level differential expression analysis for single-cell RNA-seq data
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Journal Article
IDEAS: individual level differential expression analysis for single-cell RNA-seq data
2022
Overview
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.
Publisher
BioMed Central,Springer Nature B.V,BMC
Subject
/ Autism
/ Autistic Disorder - genetics
/ Autistic Disorder - metabolism
/ Autistic Disorder - pathology
/ Biomedical and Life Sciences
/ COVID-19
/ Datasets
/ genes
/ Humans
/ IDEAS
/ Method
/ Methods
/ Microbial Genetics and Genomics
/ Nerve Tissue Proteins - classification
/ Nerve Tissue Proteins - genetics
/ Nerve Tissue Proteins - metabolism
/ Sequence Analysis, RNA - methods
/ Single-Cell Analysis - methods
/ Software
