ArticleGenetic epidemiology2014
Robust rare variant association testing for quantitative traits in samples with related individuals.
Article in Genetic epidemiology, 2014. 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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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
38 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry.Genome medicine · 2023Pooled it
- A generalized test of genotype-phenotype causality in population-sampled nuclear families.PLoS genetics · 2026Article
- JASPER: Fast, powerful, multitrait association testing in structured samples gives insight on pleiotropy in gene expression.American journal of human genetics · 2024Article
- Rare variants at KCNJ2 are associated with LDL-cholesterol levels in a cross-population study.NPJ genomic medicine · 2024Article
- JASPER: fast, powerful, multitrait association testing in structured samples gives insight on pleiotropy in gene expression.bioRxiv : the preprint server for biology · 2023Article
- A novel rare variants association test for binary traits in family-based designs via copulas.Statistical methods in medical research · 2023Article
- Family history aggregation unit-based tests to detect rare genetic variant associations with application to the Framingham Heart Study.American journal of human genetics · 2022Article
- Insights into the genetic architecture of haematological traits from deep phenotyping and whole-genome sequencing for two Mediterranean isolated populations.Scientific reports · 2022Observational
- Whole-genome sequencing analysis of the cardiometabolic proteome.Nature communications · 2020Article
- Gene-Based Association Mapping for Dental Caries in The GENEVA Consortium.Journal of dentistry and dental medicine · 2020Article
- Review
- A generalized model for combining dependent SNP-level summary statistics and its extensions to statistics of other levels.Scientific reports · 2019Article
- Efficient Variant Set Mixed Model Association Tests for Continuous and Binary Traits in Large-Scale Whole-Genome Sequencing Studies.American journal of human genetics · 2019Article
- Discovery of rare variants implicated in schizophrenia using next-generation sequencing.Journal of translational genetics and genomics · 2019Article
- Article
- Robust Rare-Variant Association Tests For Quantitative Traits in General Pedigrees.Statistics in biosciences · 2018Article
- Impact of rare and low-frequency sequence variants on reliability of genomic prediction in dairy cattle.Genetics, selection, evolution : GSE · 2018Article
- Cohort-wide deep whole genome sequencing and the allelic architecture of complex traits.Nature communications · 2018Article
- Whole exome sequencing analysis in severe chronic obstructive pulmonary disease.Human molecular genetics · 2018Article
- Genetic pleiotropy between mood disorders, metabolic, and endocrine traits in a multigenerational pedigree.Translational psychiatry · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The recent development of high-throughput sequencing technologies calls for powerful statistical tests to detect rare genetic variants associated with complex human traits. Sampling related individuals in sequencing studies offers advantages over sampling unrelated individuals only, including improved protection against sequencing error, the ability to use imputation to make more efficient use of sequence data, and the possibility of power boost due to more observed copies of extremely rare alleles among relatives. With related individuals, familial correlation needs to be accounted for to ensure correct control over type I error and to improve power. Recognizing the limitations of existing rare-variant association tests for family data, we propose MONSTER (Minimum P-value Optimized Nuisance parameter Score Test Extended to Relatives), a robust rare-variant association test, which generalizes the SKAT-O method for independent samples. MONSTER uses a mixed effects model that accounts for covariates and additive polygenic effects. To obtain a powerful test, MONSTER adaptively adjusts to the unknown configuration of effects of rare-variant sites. MONSTER also offers an analytical way of assessing P-values, which is desirable because permutation is not straightforward to conduct in related samples. In simulation studies, we demonstrate that MONSTER effectively accounts for family structure, is computationally efficient and compares very favorably, in terms of power, to previously proposed tests that allow related individuals. We apply MONSTER to an analysis of high-density lipoprotein cholesterol in the Framingham Heart Study, where we are able to replicate association with three genes.
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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 Socratic graph.