ArticleScience (New York, N.Y.)2019
Genetic regulatory variation in populations informs transcriptome analysis in rare disease.
Article in Science (New York, N.Y.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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Who cites it
72 citing papers in PubMed.
- The landscape of allele-specific expression in human kidneys.Science advances · 2026Article
- Tools and tactics for studying alternative splicing.Nature reviews. Genetics · 2026Review
- LongAllele: a joint inference framework for allele-specific analysis on long-read bulk and single-cell RNA sequencing.bioRxiv : the preprint server for biology · 2026Article
- Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications.Signal transduction and targeted therapy · 2026Review
- Targeted long-read RNA sequencing for rare disease diagnosis and variant interpretation.Science advances · 2026Article
- Benchmarking RNA-seq Tools for Real-World Diagnostic Applications.Research square · 2026Article
- Benchmarking RNA-seq Tools for Real-World Diagnostic Applications.medRxiv : the preprint server for health sciences · 2026Article
- Nonlinear transcriptional responses to gradual modulation of transcription factor dosage.eLife · 2026Article
- Improved Identification of Large-effect Rare Genetic Variants using Haplotype Aggregated Allele-specific Expression Data.medRxiv : the preprint server for health sciences · 2025Article
- Approaches for identification of 5' UTR mutations impacting translation and protein production from neurodevelopmental disorder genes.Cell reports methods · 2025Article
- Recalibrating differential gene expression by genetic dosage variance prioritizes functionally relevant genes.Genome research · 2025Article
- Nonlinear transcriptional responses to gradual modulation of transcription factor dosage.bioRxiv : the preprint server for biology · 2025Article
- Allele Specific Expression Quality Control Fills Critical Gap in Transcriptome Assisted Rare Variant Interpretation.bioRxiv : the preprint server for biology · 2025Article
- RNA sequencing driven diagnosis expands the phenotypic spectrum of NBAS deficiency.Molecular genetics and metabolism · 2025Article
- Clinical validation of RNA sequencing for Mendelian disorder diagnostics.American journal of human genetics · 2025Article
- Statistical framework for calling allelic imbalance in high-throughput sequencing data.Nature communications · 2025Article
- Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research.Acta biochimica Polonica · 2025Review
- Multimodal analysis of RNA sequencing data powers discovery of complex trait genetics.Nature communications · 2024Article
- RNA Sequencing in Disease Diagnosis.Annual review of genomics and human genetics · 2024Review
- Identification of skewed X chromosome inactivation using exome and transcriptome sequencing in patients with suspected rare genetic disease.BMC genomics · 2024Article
12 more citing papers are in PubMed but not listed here.
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15 authors.
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Abstract
Transcriptome data can facilitate the interpretation of the effects of rare genetic variants. Here, we introduce ANEVA (analysis of expression variation) to quantify genetic variation in gene dosage from allelic expression (AE) data in a population. Application of ANEVA to the Genotype-Tissues Expression (GTEx) data showed that this variance estimate is robust and correlated with selective constraint in a gene. Using these variance estimates in a dosage outlier test (ANEVA-DOT) applied to AE data from 70 Mendelian muscular disease patients showed accuracy in detecting genes with pathogenic variants in previously resolved cases and led to one confirmed and several potential new diagnoses. Using our reference estimates from GTEx data, ANEVA-DOT can be incorporated in rare disease diagnostic pipelines to use RNA-sequencing data more effectively.
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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.