ArticleNature genetics2025
Transcriptome-wide analysis of differential expression in perturbation atlases.
Article in Nature genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis of the brain transcriptomes of multiple genetic mouse models of schizophrenia highlights dysregulation in striatum and thalamus.Translational psychiatry · 2025Pooled it
- Deep learning perturbation models can outperform baselines on calibrated metrics.Nature biotechnology · 2026Article
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- Foundation model reveals the shared organization of transcription and topologically associating domains.Cell systems · 2026Article
- A systematic comparison of single-cell perturbation response prediction models.Science advances · 2026Article
- A transcription factor regulatory atlas for activity inference and perturbation prediction.Nucleic acids research · 2026Article
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- Cerebrovascular vulnerability and fibrosis in human brain aneurysms.Nature neuroscience · 2026Article
- Buffering of gene dosage response curves for human complex traits.Cell genomics · 2026Article
- PertAdapt: unlocking single-cell foundation models for genetic perturbation prediction via condition-sensitive adaptation.Bioinformatics (Oxford, England) · 2026Article
- Regulatory network topology and the genetic architecture of gene expression.Cell genomics · 2026Article
- TxPert: using multiple knowledge graphs for prediction of transcriptomic perturbation effects.Nature biotechnology · 2026Article
- Concordant transcriptional and morphological remodeling revealed bybioRxiv : the preprint server for biology · 2026Article
- Inter-individual variation of cellular and gene-expression properties of the human striatum.bioRxiv : the preprint server for biology · 2026Article
- Mesoscale molecular architecture of the human striatum across cell types and lifespan.bioRxiv : the preprint server for biology · 2026Article
- Clinical,medRxiv : the preprint server for health sciences · 2026Article
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- Virtual Cells Need Context, Not Just Scale.bioRxiv : the preprint server for biology · 2026Article
- Isoform-specific single-cell perturb-seq reveals distinct functions of alternative promoters in drug response.Nucleic acids research · 2026Article
- Article
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Abstract
Single-cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of genetic perturbations at scale. However, the data produced by these screens are noisy, and many effects may go undetected. Here we introduce transcriptome-wide analysis of differential expression (TRADE)-a statistical model for the distribution of true differential expression effects that accounts for estimation error appropriately. TRADE estimates the 'transcriptome-wide impact', which quantifies the total effect of a perturbation across the transcriptome. Analyzing several large Perturb-seq datasets, we show that many transcriptional effects remain undetected in standard analyses but emerge in aggregate using TRADE. A typical gene perturbation affects an estimated 45 genes, whereas a typical essential gene affects over 500. We find moderate consistency of perturbation effects across cell types, identify perturbations where transcriptional responses vary qualitatively across dosage levels and clarify the relationship between genetic and transcriptomic correlations across neuropsychiatric disorders.
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