ArticleAmerican journal of human genetics2017
Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data.
Article in American journal of human genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.
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Who cites it
38 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Review of Statistical Methods for Identifying Trait-Relevant Tissues and Cell Types.Frontiers in genetics · 2020Pooled it
- An empirical Bayes framework for burden and dispersion association tests helps prioritize rare variants associated with Alzheimer's disease.medRxiv : the preprint server for health sciences · 2026Article
- Integrating common and rare variants improves polygenic risk prediction across diverse populations.Nature communications · 2026Article
- MIRAGE: A Bayesian statistical method for gene-level rare-variant analysis incorporating functional annotations.American journal of human genetics · 2026Article
- iRUNNER: A Baseline Mutation Burden Regression for Identifying Gene Interaction Between Rare Variants for Diseases.Genomics, proteomics & bioinformatics · 2025Article
- Leveraging functional annotations to map rare variants associated with Alzheimer disease with gruyere.American journal of human genetics · 2025Article
- RetroFun-RVS: A Retrospective Family-Based Framework for Rare Variant Analysis Incorporating Functional Annotations.Genetic epidemiology · 2025Article
- The goldmine of GWAS summary statistics: a systematic review of methods and tools.BioData mining · 2024Article
- Article
- Meta-analysis of set-based multiple phenotype association test based on GWAS summary statistics from different cohorts.Frontiers in genetics · 2024Article
- ZINQ-L: a zero-inflated quantile approach for differential abundance analysis of longitudinal microbiome data.Frontiers in genetics · 2024Article
- Accurate and efficient estimation of local heritability using summary statistics and the linkage disequilibrium matrix.Nature communications · 2023Article
- An allelic-series rare-variant association test for candidate-gene discovery.American journal of human genetics · 2023Article
- Cis-regulatory hubs: a new 3D model of complex disease genetics with an application to schizophrenia.Life science alliance · 2022Article
- Recent advances and challenges of rare variant association analysis in the biobank sequencing era.Frontiers in genetics · 2022Review
- ZERO-INFLATED QUANTILE RANK-SCORE BASED TEST (ZIQRANK) WITH APPLICATION TO SCRNA-SEQ DIFFERENTIAL GENE EXPRESSION ANALYSIS.The annals of applied statistics · 2021Article
- Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Powerful and robust non-parametric association testing for microbiome data via a zero-inflated quantile approach (ZINQ).Microbiome · 2021Article
- Quantitative disease risk scores from EHR with applications to clinical risk stratification and genetic studies.NPJ digital medicine · 2021Article
- Rare variants regulate expression of nearby individual genes in multiple tissues.PLoS genetics · 2021Article
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4 authors.
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Abstract
Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests.
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