ArticleCell reports methods2023
Atlas of primary cell-type-specific sequence models of gene expression and variant effects.
Article in Cell reports methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Spatiotemporal AI-based modeling of gene regulation and variant effects in the developing human brain using Seal.Nature neuroscience · 2026Article
- HiFIseek: Gene-specific enrichment of high-impact mutations in associated genomic regions.PLoS computational biology · 2026Article
- Mapping functional non-coding variation in individual human genomes through haplotyping, multiomics, and deep learning.Nature communications · 2026Article
- EpiExpr: Predicting gene expression using epigenetic data and chromatin interactions.bioRxiv : the preprint server for biology · 2026Article
- Structural variants in human congenital heart disease disrupt distal genomic regulatory contacts of developmental genes.bioRxiv : the preprint server for biology · 2026Article
- HumanBase: an interactive AI platform for human biology.Nature methods · 2026Article
- Computational strategies for cross-species knowledge transfer.Nature methods · 2026Review
- Gene-centered representation of coding and regulatory variation enables outcome prediction.bioRxiv : the preprint server for biology · 2026Article
- Preliminary examination of noncoding mutations of esophageal squamous cell carcinoma in African Americans.Frontiers in genetics · 2026Article
- An Evidence-Grounded Research Assistant for Functional Genomics and Drug Target Assessment.bioRxiv : the preprint server for biology · 2025Article
- Advances and applications in single-cell and spatial genomics.Science China. Life sciences · 2025Review
- Article
- Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.Human genomics · 2024Article
- Computational strategies for cross-species knowledge transfer and translational biomedicine.ArXiv · 2024Article
- Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors.bioRxiv : the preprint server for biology · 2024Article
- Mapping Cell Atlases at the Single-Cell Level.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Human biology is rooted in highly specialized cell types programmed by a common genome, 98% of which is outside of genes. Genetic variation in the enormous noncoding space is linked to the majority of disease risk. To address the problem of linking these variants to expression changes in primary human cells, we introduce ExPectoSC, an atlas of modular deep-learning-based models for predicting cell-type-specific gene expression directly from sequence. We provide models for 105 primary human cell types covering 7 organ systems, demonstrate their accuracy, and then apply them to prioritize relevant cell types for complex human diseases. The resulting atlas of sequence-based gene expression and variant effects is publicly available in a user-friendly interface and readily extensible to any primary cell types. We demonstrate the accuracy of our approach through systematic evaluations and apply the models to prioritize ClinVar clinical variants of uncertain significance, verifying our top predictions experimentally.
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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.