ArticlePLoS genetics2010
A novel adaptive method for the analysis of next-generation sequencing data to detect complex trait associations with rare variants due to gene main effects and interactions.
Article in PLoS genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 156 papers, 2 of them syntheses 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
156 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Association Analysis and Meta-Analysis of Multi-Allelic Variants for Large-Scale Sequence Data.Genes · 2020Pooled it
- Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits.Current protocols in human genetics · 2019Pooled it
- Rare Functional Variants Associated with Antidepressant Remission in Mexican-Americans: Short title: Antidepressant remission and pharmacogenetics in Mexican-Americans.Journal of affective disorders · 2021Trial
- Archipelago Method for Variant Set Association Test Statistics.Genetic epidemiology · 2026Article
- iRUNNER: A Baseline Mutation Burden Regression for Identifying Gene Interaction Between Rare Variants for Diseases.Genomics, proteomics & bioinformatics · 2025Article
- Rare-variant association studies: When are aggregation tests more powerful than single-variant tests?American journal of human genetics · 2025Article
- Article
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- A Case-Control Study Supports Genetic Contribution of theAntioxidants (Basel, Switzerland) · 2024Article
- Genome-Wide Gene-Environment Interaction Analysis Identifies Novel Candidate Variants for Growth Traits in Beef Cattle.Animals : an open access journal from MDPI · 2024Article
- Genetic Rare Variants Affecting Multiple Pathways in Japanese Patients with Palindromic Rheumatism.The Kobe journal of medical sciences · 2024Article
- Review
- Excalibur: A new ensemble method based on an optimal combination of aggregation tests for rare-variant association testing for sequencing data.PLoS computational biology · 2023Article
- Next-Generation Sequencing Data-Based Association Testing of a Group of Genetic Markers for Complex Responses Using a Generalized Linear Model Framework.Mathematics (Basel, Switzerland) · 2023Article
- Examination of Genetic Susceptibility in Radiation-Associated Meningioma.Radiation research · 2022Article
- Deviation from baseline mutation burden provides powerful and robust rare-variants association test for complex diseases.Nucleic acids research · 2022Article
- Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy.Journal of personalized medicine · 2022Review
- Genetics in parkinson's disease: From better disease understanding to machine learning based precision medicine.Frontiers in molecular medicine · 2022Review
- Resequencing of candidate genes for Keratoconus reveals a role for Ehlers-Danlos Syndrome genes.European journal of human genetics : EJHG · 2021Article
- Could the Epigenetics of Eosinophils in Asthma and Allergy Solve Parts of the Puzzle?International journal of molecular sciences · 2021Review
96 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
There is solid evidence that rare variants contribute to complex disease etiology. Next-generation sequencing technologies make it possible to uncover rare variants within candidate genes, exomes, and genomes. Working in a novel framework, the kernel-based adaptive cluster (KBAC) was developed to perform powerful gene/locus based rare variant association testing. The KBAC combines variant classification and association testing in a coherent framework. Covariates can also be incorporated in the analysis to control for potential confounders including age, sex, and population substructure. To evaluate the power of KBAC: 1) variant data was simulated using rigorous population genetic models for both Europeans and Africans, with parameters estimated from sequence data, and 2) phenotypes were generated using models motivated by complex diseases including breast cancer and Hirschsprung's disease. It is demonstrated that the KBAC has superior power compared to other rare variant analysis methods, such as the combined multivariate and collapsing and weight sum statistic. In the presence of variant misclassification and gene interaction, association testing using KBAC is particularly advantageous. The KBAC method was also applied to test for associations, using sequence data from the Dallas Heart Study, between energy metabolism traits and rare variants in ANGPTL 3,4,5 and 6 genes. A number of novel associations were identified, including the associations of high density lipoprotein and very low density lipoprotein with ANGPTL4. The KBAC method is implemented in a user-friendly R package.
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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 OpenQuestion graph.