ArticleNature communications2020
Multi-trait analysis of rare-variant association summary statistics using MTAR.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- Meta-analysis of six dairy cattle breeds reveals biologically relevant candidate genes for mastitis resistance.Genetics, selection, evolution : GSE · 2024Pooled it
- Genomics of drug target prioritization for complex diseases.Nature reviews. Genetics · 2026Review
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- A scalable framework for identifying allelic series from summary statistics.American journal of human genetics · 2025Article
- A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies.Nature computational science · 2025Article
- Identification of genetic basis of brain imaging by group sparse multi-task learning leveraging summary statistics.Computational and structural biotechnology journal · 2024Article
- The goldmine of GWAS summary statistics: a systematic review of methods and tools.BioData mining · 2024Article
- Shared Genetic Architectures between Coronary Artery Disease and Type 2 Diabetes Mellitus in East Asian and European Populations.Biomedicines · 2024Article
- Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study.Nature communications · 2024Article
- Applying polygenic risk score methods to pharmacogenomics GWAS: challenges and opportunities.Briefings in bioinformatics · 2023Article
- A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies.bioRxiv : the preprint server for biology · 2023Article
- New statistical selection method for pleiotropic variants associated with both quantitative and qualitative traits.BMC bioinformatics · 2023Article
- A comprehensive comparison of multilocus association methods with summary statistics in genome-wide association studies.BMC bioinformatics · 2022Article
- sumSTAAR: A flexible framework for gene-based association studies using GWAS summary statistics.PLoS computational biology · 2022Article
- Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy.Journal of personalized medicine · 2022Review
- Recent advances and challenges of rare variant association analysis in the biobank sequencing era.Frontiers in genetics · 2022Review
- The impact of violating the independence assumption in meta-analysis on biomarker discovery.Frontiers in genetics · 2022Article
- An Omnibus Test for Detecting Multiple Phenotype Associations Based on GWAS Summary Level Data.Frontiers in genetics · 2021Article
- Genetic mapping of developmental trajectories for complex traits and diseases.Computational and structural biotechnology journal · 2021Article
- Breeding for Climate Change Resilience: A Case Study of Loblolly Pine (Frontiers in plant science · 2021Review
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Integrating association evidence across multiple traits can improve the power of gene discovery and reveal pleiotropy. Most multi-trait analysis methods focus on individual common variants in genome-wide association studies. Here, we introduce multi-trait analysis of rare-variant associations (MTAR), a framework for joint analysis of association summary statistics between multiple rare variants and different traits. MTAR achieves substantial power gain by leveraging the genome-wide genetic correlation measure to inform the degree of gene-level effect heterogeneity across traits. We apply MTAR to rare-variant summary statistics for three lipid traits in the Global Lipids Genetics Consortium. 99 genome-wide significant genes were identified in the single-trait-based tests, and MTAR increases this to 139. Among the 11 novel lipid-associated genes discovered by MTAR, 7 are replicated in an independent UK Biobank GWAS analysis. Our study demonstrates that MTAR is substantially more powerful than single-trait-based tests and highlights the value of MTAR for novel gene discovery.
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