ArticleGenetic epidemiology2014
Summary of results and discussions from the gene-based tests group at Genetic Analysis Workshop 18.
Article in Genetic epidemiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Comparison of haplotype-based statistical tests for disease association with rare and common variants.Briefings in bioinformatics · 2016Article
- A Sequence Kernel Association Test for Dichotomous Traits in Family Samples under a Generalized Linear Mixed Model.Human heredity · 2015Article
- Rare-Variant Kernel Machine Test for Longitudinal Data from Population and Family Samples.Human heredity · 2015Article
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1 author.
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Abstract
I present a summary of the results and discussions held within the working group on gene-based tests at Genetic Analysis Workshop 18 (GAW18). The main focus of interest in our working group was modeling the action of combinations or "groups" of genetic variants, with a group of variants most often defined as a set of single-nucleotide polymorphisms lying within a known gene. Some contributions investigated the performance of previously proposed methods (particularly rare variant collapsing or burden-type methods) for addressing this question, applied to the GAW18 data, and other contributions developed novel approaches and addressed novel questions. Most approaches were successful in detecting significant effects at MAP4 in the simulated data. No other genetic effects were consistently detected across different analyses. Low power was noted, particularly for those methods that restricted analysis to purely the subset of unrelated individuals.
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