ArticleNature communications2023
OTTERS: a powerful TWAS framework leveraging summary-level reference data.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it.
- GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis.Genome research · 2024Pooled it
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- Retinal Transcriptome-Wide Association Study Identifies Novel Alzheimer's Disease Risk Genes.medRxiv : the preprint server for health sciences · 2026Article
- Integrating dorsolateral prefrontal cortex multi-omics and GWAS summary data reveals genetic etiology of Parkinson's disease.Research square · 2026Article
- Integrating dorsolateral prefrontal cortex multi-omics and GWAS summary data reveals genetic etiology of Parkinson's disease.medRxiv : the preprint server for health sciences · 2026Article
- Single-cell multi-omic integration analysis prioritizes druggable genes and reveals cell-type-specific causal effects in glioblastomagenesis.Journal of translational medicine · 2026Article
- Cell-type-aware transcriptome-wide association studies identify 91 independent risk genes for Alzheimer's disease dementia.Communications biology · 2026Article
- Multi-ancestry transcriptome prediction with functionally informed variants in TOPMed MESA improves performance of transcriptome-wide association studies.American journal of human genetics · 2026Article
- Single-cell expression QTL analyses of the human cerebellum reveal vulnerability of oligodendrocytes in essential tremor.Nature genetics · 2026Article
- Multi-tissue transcriptome-wide association study identifies 29 risk genes associated with attention-deficit/hyperactivity disorder.medRxiv : the preprint server for health sciences · 2026Article
- Key genes and pathway differences between serrated polyps and conventional adenomas: insights from multi-omics.Translational cancer research · 2026Article
- Transcriptome-wide association studies at cell-state level using single-cell eQTL data.Cell genomics · 2026Article
- ASTWAS: modeling alternative polyadenylation and SNP effects in kernel-driven TWAS reveal novel genetic associations for complex traits.Briefings in bioinformatics · 2026Article
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- Monocyte inflammation and resilience to Alzheimer's disease: novel genetic risk genes identified by transcriptome-wide association study.Translational psychiatry · 2025Article
- The role of hypothyroidism in cirrhosis pathogenesis: A retrospective cohort study and multi-omics integration analysis.PLoS genetics · 2025Article
- Exploring Contraindicated Medications and Corresponding Targeted Genes for Migraine Through Integrated Genetic Approaches.Brain and behavior · 2025Article
- Cross-tissue transcriptome-wide analysis reveals novel insights into thyroid cancer etiology.Discover oncology · 2025Article
- CADET: Enhanced transcriptome-wide association analyses in admixed samples using eQTL summary data.American journal of human genetics · 2025Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Most existing TWAS tools require individual-level eQTL reference data and thus are not applicable to summary-level reference eQTL datasets. The development of TWAS methods that can harness summary-level reference data is valuable to enable TWAS in broader settings and enhance power due to increased reference sample size. Thus, we develop a TWAS framework called OTTERS (Omnibus Transcriptome Test using Expression Reference Summary data) that adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level eQTL reference data and conducts an omnibus TWAS. We show that OTTERS is a practical and powerful TWAS tool by both simulations and application studies.
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