ArticlePLoS genetics2016
Testing Rare-Variant Association without Calling Genotypes Allows for Systematic Differences in Sequencing between Cases and Controls.
Article in PLoS genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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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
24 citing papers in PubMed.
- Genetic diversity and relationship of Bugesera and Rwamagana indigenous chicken populations with SASSO chickens using DArTseq SNPs.PloS one · 2025Article
- Integrated Genomic Approaches to Elucidate the Genetic Basis of Brugada Syndrome in Taiwanese Patients.Bioinformatics and biology insights · 2025Article
- Effectiveness of DArTseq markers application in genetic diversity and population structure of indigenous chickens in Eastern Province of Rwanda.BMC genomics · 2024Article
- Integrating External Controls by Regression Calibration for Genome-Wide Association Study.Genes · 2024Article
- Case-only exome variation analysis of severe alcohol dependence using a multivariate hierarchical gene clustering approach.PloS one · 2023Article
- Opportunities and challenges for the use of common controls in sequencing studies.Nature reviews. Genetics · 2022Review
- Integrating external controls in case-control studies improves power for rare-variant tests.Genetic epidemiology · 2022Article
- A data harmonization pipeline to leverage external controls and boost power in GWAS.Human molecular genetics · 2022Article
- NGS allele counts versus called genotypes for testing genetic association.Computational and structural biotechnology journal · 2022Article
- Recent advances and challenges of rare variant association analysis in the biobank sequencing era.Frontiers in genetics · 2022Review
- Sub-genic intolerance, ClinVar, and the epilepsies: A whole-exome sequencing study of 29,165 individuals.American journal of human genetics · 2021Article
- Novel score test to increase power in association test by integrating external controls.Genetic epidemiology · 2021Article
- Joint analysis of single-cell and bulk tissue sequencing data to infer intratumor heterogeneity.Biometrics · 2020Article
- VikNGS: a C++ variant integration kit for next generation sequencing association analysis.Bioinformatics (Oxford, England) · 2020Article
- Rare-variant collapsing analyses for complex traits: guidelines and applications.Nature reviews. Genetics · 2019Review
- Allele balance bias identifies systematic genotyping errors and false disease associations.Human mutation · 2019Article
- Association analysis using somatic mutations.PLoS genetics · 2018Article
- Project MinE: study design and pilot analyses of a large-scale whole-genome sequencing study in amyotrophic lateral sclerosis.European journal of human genetics : EJHG · 2018Article
- Robust inference of population structure from next-generation sequencing data with systematic differences in sequencing.Bioinformatics (Oxford, England) · 2018Article
- Genome-wide linkage and association study implicates the 10q26 region as a major genetic contributor to primary nonsyndromic vesicoureteric reflux.Scientific reports · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Next-generation sequencing of DNA provides an unprecedented opportunity to discover rare genetic variants associated with complex diseases and traits. However, the common practice of first calling underlying genotypes and then treating the called values as known is prone to false positive findings, especially when genotyping errors are systematically different between cases and controls. This happens whenever cases and controls are sequenced at different depths, on different platforms, or in different batches. In this article, we provide a likelihood-based approach to testing rare variant associations that directly models sequencing reads without calling genotypes. We consider the (weighted) burden test statistic, which is the (weighted) sum of the score statistic for assessing effects of individual variants on the trait of interest. Because variant locations are unknown, we develop a simple, computationally efficient screening algorithm to estimate the loci that are variants. Because our burden statistic may not have mean zero after screening, we develop a novel bootstrap procedure for assessing the significance of the burden statistic. We demonstrate through extensive simulation studies that the proposed tests are robust to a wide range of differential sequencing qualities between cases and controls, and are at least as powerful as the standard genotype calling approach when the latter controls type I error. An application to the UK10K data reveals novel rare variants in gene BTBD18 associated with childhood onset obesity. The relevant software is freely available.
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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.