ArticleHuman heredity2012
ARIEL and AMELIA: testing for an accumulation of rare variants using next-generation sequencing data.
Article in Human heredity, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
- A three-groups non-local model for combining heterogeneous data sources to identify genes associated with Parkinson's disease.Biometrics · 2026Article
- Rare-variant association studies: When are aggregation tests more powerful than single-variant tests?American journal of human genetics · 2025Article
- Whole-exome sequencing and Drosophila modelling reveal mutated genes and pathways contributing to human ovarian failure.Reproductive biology and endocrinology : RB&E · 2024Article
- Evolutionarily new genes in humans with disease phenotypes reveal functional enrichment patterns shaped by adaptive innovation and sexual selection.bioRxiv : the preprint server for biology · 2024Article
- DYNATE: Localizing rare-variant association regions via multiple testing embedded in an aggregation tree.Genetic epidemiology · 2024Article
- Evolutionarily new genes in humans with disease phenotypes reveal functional enrichment patterns shaped by adaptive innovation and sexual selection.Research square · 2023Article
- 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
- Impact of pre- and post-variant filtration strategies on imputation.Scientific reports · 2021Article
- AeQTL: eQTL analysis using region-based aggregation of rare genomic variants.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2021Article
- 'There and Back Again'-Forward Genetics and Reverse Phenotyping in Pulmonary Arterial Hypertension.Genes · 2020Review
- The role of genomics and genetics in pulmonary arterial hypertension.Global cardiology science & practice · 2020Review
- Rare-variant collapsing analyses for complex traits: guidelines and applications.Nature reviews. Genetics · 2019Review
- A powerful and data-adaptive test for rare-variant-based gene-environment interaction analysis.Statistics in medicine · 2019Article
- Learning the optimal scale for GWAS through hierarchical SNP aggregation.BMC bioinformatics · 2018Article
- On the substructure controls in rare variant analysis: Principal components or variance components?Genetic epidemiology · 2018Article
- Human Genome Sequencing at the Population Scale: A Primer on High-Throughput DNA Sequencing and Analysis.American journal of epidemiology · 2017Review
- The impact of rare and low-frequency genetic variants in common disease.Genome biology · 2017Review
- Opportunities and challenges of whole-genome and -exome sequencing.BMC genetics · 2017Review
- Discovery of rare variants for complex phenotypes.Human genetics · 2016Review
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4 authors.
Funding
Abstract
objectivesThere is increasing evidence that rare variants play a role in some complex traits, but their analysis is not straightforward. Locus-based tests become necessary due to low power in rare variant single-point association analyses. In addition, variant quality scores are available for sequencing data, but are rarely taken into account. Here, we propose two locus-based methods that incorporate variant quality scores: a regression-based collapsing approach and an allele-matching method.
methodsUsing simulated sequencing data we compare 4 locus-based tests of trait association under different scenarios of data quality. We test two collapsing-based approaches and two allele-matching-based approaches, taking into account variant quality scores and ignoring variant quality scores. We implement the collapsing and allele-matching approaches accounting for variant quality in the freely available ARIEL and AMELIA software.
resultsThe incorporation of variant quality scores in locus-based association tests has power advantages over weighting each variant equally. The allele-matching methods are robust to the presence of both protective and risk variants in a locus, while collapsing methods exhibit a dramatic loss of power in this scenario.
conclusionsThe incorporation of variant quality scores should be a standard protocol when performing locus-based association analysis on sequencing data. The ARIEL and AMELIA software implement collapsing and allele-matching locus association analysis methods, respectively, that allow the incorporation of variant quality scores.
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