ArticlePloS one2014
Association testing of clustered rare causal variants in case-control studies.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Data-driven modelling of mutational hotspots and in silico predictors in hypertrophic cardiomyopathy.Journal of medical genetics · 2021Article
- Identifying individual risk rare variants using protein structure guided local tests (POINT).PLoS computational biology · 2019Article
- GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.BMC systems biology · 2018Article
- The impact of a fine-scale population stratification on rare variant association test results.PloS one · 2018Article
- Extreme Trait Whole-Genome Sequencing Identifies PTPRO as a Novel Candidate Gene in Emphysema with Severe Airflow Obstruction.American journal of respiratory and critical care medicine · 2017Article
- DoEstRare: A statistical test to identify local enrichments in rare genomic variants associated with disease.PloS one · 2017Article
- Conditioning adaptive combination of P-values method to analyze case-parent trios with or without population controls.Scientific reports · 2016Article
- Beyond Rare-Variant Association Testing: Pinpointing Rare Causal Variants in Case-Control Sequencing Study.Scientific reports · 2016Article
- Assessing the Power of Exome Chips.PloS one · 2015Article
- Adaptive combination of P-values for family-based association testing with sequence data.PloS one · 2014Article
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1 author.
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Abstract
Biological evidence suggests that multiple causal variants in a gene may cluster physically. Variants within the same protein functional domain or gene regulatory element would locate in close proximity on the DNA sequence. However, spatial information of variants is usually not used in current rare variant association analyses. We here propose a clustering method (abbreviated as "CLUSTER"), which is extended from the adaptive combination of P-values. Our method combines the association signals of variants that are more likely to be causal. Furthermore, the statistic incorporates the spatial information of variants. With extensive simulations, we show that our method outperforms several commonly-used methods in many scenarios. To demonstrate its use in real data analyses, we also apply this CLUSTER test to the Dallas Heart Study data. CLUSTER is among the best methods when the effects of causal variants are all in the same direction. As variants located in close proximity are more likely to have similar impact on disease risk, CLUSTER is recommended for association testing of clustered rare causal variants in case-control studies.
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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.