ArticleAmerican journal of human genetics2010
Extending rare-variant testing strategies: analysis of noncoding sequence and imputed genotypes.
Article in American journal of human genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers, 2 of them syntheses that pooled it.
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Who cites it
81 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Rare variants in BRCA2 and CHEK2 are associated with the risk of urinary tract cancers.Scientific reports · 2016Pooled it
- Meta-analysis of gene-level tests for rare variant association.Nature genetics · 2014Pooled it
- 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
- Genetics in parkinson's disease: From better disease understanding to machine learning based precision medicine.Frontiers in molecular medicine · 2022Review
- Targeted resequencing showing novel common and rare genetic variants increases the risk of asthma in the Chinese Han population.Journal of clinical laboratory analysis · 2021Article
- Robust Rare-Variant Association Tests For Quantitative Traits in General Pedigrees.Statistics in biosciences · 2018Article
- Testing an optimally weighted combination of common and/or rare variants with multiple traits.PloS one · 2018Article
- PreCimp: Pre-collapsing imputation approach increases imputation accuracy of rare variants in terms of collapsed variables.Genetic epidemiology · 2017Article
- A non-threshold region-specific method for detecting rare variants in complex diseases.PloS one · 2017Article
- Illustrating, Quantifying, and Correcting for Bias in Post-hoc Analysis of Gene-Based Rare Variant Tests of Association.Frontiers in genetics · 2017Article
- A Nonparametric Regression Approach to Control for Population Stratification in Rare Variant Association Studies.Scientific reports · 2016Article
- Joint Analysis of Multiple Traits in Rare Variant Association Studies.Annals of human genetics · 2016Article
- Genome-wide joint analysis of single-nucleotide variant sets and gene expression for hypertension and related phenotypes.BMC proceedings · 2016Article
- Article
- Rare variants analysis using penalization methods for whole genome sequence data.BMC bioinformatics · 2015Article
- Strategies for Imputing and Analyzing Rare Variants in Association Studies.Trends in genetics : TIG · 2015Review
- Insights into blood lipids from rare variant discovery.Current opinion in genetics & development · 2015Review
- Massively parallel quantification of the regulatory effects of noncoding genetic variation in a human cohort.Genome research · 2015Article
- Robust and Powerful Affected Sibpair Test for Rare Variant Association.Genetic epidemiology · 2015Article
- Variation in complement protein C1q is not a major contributor to cognitive impairment in Parkinson's disease.Neuroscience letters · 2015Article
21 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Next Generation Sequencing Technology has revolutionized our ability to study the contribution of rare genetic variation to heritable traits. However, existing single-marker association tests are underpowered for detecting rare risk variants. A more powerful approach involves pooling methods that combine multiple rare variants from the same gene into a single test statistic. Proposed pooling methods can be limited because they generally assume high-quality genotypes derived from deep-coverage sequencing, which may not be available. In this paper, we consider an intuitive and computationally efficient pooling statistic, the cumulative minor-allele test (CMAT). We assess the performance of the CMAT and other pooling methods on datasets simulated with population genetic models to contain realistic levels of neutral variation. We consider study designs ranging from exon-only to whole-gene analyses that contain noncoding variants. For all study designs, the CMAT achieves power comparable to that of previously proposed methods. We then extend the CMAT to probabilistic genotypes and describe application to low-coverage sequencing and imputation data. We show that augmenting sequence data with imputed samples is a practical method for increasing the power of rare-variant studies. We also provide a method of controlling for confounding variables such as population stratification. Finally, we demonstrate that our method makes it possible to use external imputation templates to analyze rare variants imputed into existing GWAS datasets. As proof of principle, we performed a CMAT analysis of more than 8 million SNPs that we imputed into the GAIN psoriasis dataset by using haplotypes from the 1000 Genomes Project.
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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.