ArticleGenome biology2022
IDEAS: individual level differential expression analysis for single-cell RNA-seq data.
Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed, 54 citations in OpenAlex.
- RKMR: A Rapid Kernel Machine Regression Framework for Optimal Marker Detection in Spatial Omics Data.bioRxiv : the preprint server for biology · 2026Article
- HopRatio: Profiling single-sample transcriptomic dysregulation using stable gene-ordering relationships.iScience · 2026Article
- Decoding Immune Regulation: From Genetic Variation to Mechanism Through Single-Cell Genomics.Immune network · 2026Review
- Trajectory-guided dimensionality reduction for multi-sample single-cell RNA-seq data reveals biologically relevant sample-level heterogeneity.Bioinformatics (Oxford, England) · 2026Article
- Leveraging Single-Cell Technologies to Advance Understanding of Myocardial Disease.Circulation research · 2026Review
- distQTL: distribution quantitative trait loci identification by population-scale single-cell data.NAR genomics and bioinformatics · 2025Article
- CBKMR: A Copula-based Bayesian Kernel Machine Regression Framework for Optimal Marker Detection in Omics Data.bioRxiv : the preprint server for biology · 2025Article
- Differential detection workflows for multi-sample single-cell RNA-seq data.BMC genomics · 2025Article
- distQTL: Distribution Quantitative Trait Loci Identification by Population-Scale Single-Cell Data.bioRxiv : the preprint server for biology · 2025Article
- scDETECT: a novel statistical model accounting for cell type correlation in single-cell RNA-seq differential expression analysis.Briefings in bioinformatics · 2025Article
- Human CLOCK enhances neocortical function.Nature neuroscience · 2025Article
- cytoKernel: robust kernel embeddings for assessing differential expression of single-cell data.Bioinformatics (Oxford, England) · 2025Article
- Causal Inference for Genomic Data with Multiple Heterogeneous Outcomes.Journal of the American Statistical Association · 2025Article
- DiSC: a statistical tool for fast differential expression analysis of individual-level single-cell RNA-seq data.Bioinformatics (Oxford, England) · 2025Article
- DeepExDC interprets genomic compartmentalization changes in single-cell Hi-C data.Briefings in bioinformatics · 2025Article
- Biases in machine-learning models of human single-cell data.Nature cell biology · 2025Review
- Dissecting tumor cell programs through group biology estimation in clinical single-cell transcriptomics.Nature communications · 2025Article
- Single-cell omics: experimental workflow, data analyses and applications.Science China. Life sciences · 2025Review
- Predicting and comparing transcription start sites in single cell populations.PLoS computational biology · 2025Article
- Single-cell sequencing in molecular diagnostics: Transformative yet untapped potential.Frontiers in genetics · 2025Review
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.