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

Genome Biol. 2022 Jan 24;23(1):33. doi: 10.1186/s13059-022-02605-1.

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: Differential expression; IDEAS; scRNA-seq.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Autistic Disorder / genetics*
  • Autistic Disorder / metabolism
  • Autistic Disorder / pathology
  • COVID-19 / genetics*
  • COVID-19 / metabolism
  • COVID-19 / pathology
  • COVID-19 / virology
  • Case-Control Studies
  • Gene Expression Profiling
  • Gene Expression Regulation
  • Humans
  • Microglia / metabolism
  • Microglia / pathology
  • Nerve Tissue Proteins / classification
  • Nerve Tissue Proteins / genetics
  • Nerve Tissue Proteins / metabolism
  • SARS-CoV-2 / pathogenicity
  • Sequence Analysis, RNA / methods*
  • Severity of Illness Index
  • Single-Cell Analysis / methods*
  • Software*
  • Whole Exome Sequencing

Substances

  • Nerve Tissue Proteins