ArticleFrontiers in genetics2012
Localization of association signal from risk and protective variants in sequencing studies.
Article in Frontiers in genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Exome-wide rare variant analyses of two bone mineral density phenotypes: the challenges of analyzing rare genetic variation.Scientific reports · 2018Article
- Prioritizing rare variants with conditional likelihood ratios.Human heredity · 2015Article
- A robust GWSS method to simultaneously detect rare and common variants for complex disease.PloS one · 2015Article
- Critical assessment of coalescent simulators in modeling recombination hotspots in genomic sequences.BMC bioinformatics · 2014Article
- Exploring the potential benefits of stratified false discovery rates for region-based testing of association with rare genetic variation.Frontiers in genetics · 2014Article
- Contribution of FKBP5 genetic variation to gemcitabine treatment and survival in pancreatic adenocarcinoma.PloS one · 2013Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Aggregating information across multiple variants in a gene or region can improve power for rare variant association testing. Power is maximized when the aggregation region contains many causal variants and few neutral variants. In this paper, we present a method for the localization of the association signal in a region using a sliding-window based approach to rare variant association testing in a region. We first introduce a novel method for analysis of rare variants, the Difference in Minor Allele Frequency test (DMAF), which allows combined analysis of common and rare variants, and makes no assumptions about the direction of effects. In whole-region analyses of simulated data with risk and protective variants, DMAF and other methods which pool data across individuals were found to outperform methods which pool data across variants. We then implement a sliding-window version of DMAF, using a step-down permutation approach to control type I error with the testing of multiple windows. In simulations, the sliding-window DMAF improved power to detect a causal sub-region, compared to applying DMAF to the whole region. Sliding-window DMAF was also effective in localizing the causal sub-region. We also applied the DMAF sliding-window approach to test for an association between response to the drug gemcitabine and variants in the gene FKBP5 sequenced in 91 lymphoblastoid cell lines derived from white non-Hispanic individuals. The application of the sliding-window test procedure detected an association in a sub-region spanning an exon and two introns, when rare and common variants were analyzed together.
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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.