Testing for an unusual distribution of rare variants

Technological advances make it possible to use high-throughput sequencing as a primary discovery tool of medical genetics, specifically for assaying rare variation. Still this approach faces the analytic challenge that the influence of very rare variants can only be evaluated effectively as a group....

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Bibliographic Details
Published in:PLoS genetics 2011-03, Vol.7 (3), p.e1001322-e1001322
Main Authors: Neale, Benjamin M, Rivas, Manuel A, Voight, Benjamin F, Altshuler, David, Devlin, Bernie, Orho-Melander, Marju, Kathiresan, Sekar, Purcell, Shaun M, Roeder, Kathryn, Daly, Mark J
Format: Article
Language:English
Subjects:
Algorithms
Analysis of Variance
Autism
Cholesterol
Clinical Medicine
Computational Biology/Genomics
Computer Simulation
Data Interpretation, Statistical
Disease
DNA sequencing
Endocrinology and Diabetes
Endokrinologi och diabetes
Genetic Variation
Genetics and Genomics/Complex Traits
Genetics and Genomics/Genetics of Disease
Genetics and Genomics/Medical Genetics
Genomes
Genotype & phenotype
Heart attacks
High-Throughput Nucleotide Sequencing - statistics & numerical data
Humans
Hypotheses
Klinisk medicin
Mathematics/Statistics
Medical and Health Sciences
Medical research
Medicin och hälsovetenskap
Methods
Models, Statistical
Mutation
Nucleotide sequencing
Single nucleotide polymorphisms
Studies
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Summary:Technological advances make it possible to use high-throughput sequencing as a primary discovery tool of medical genetics, specifically for assaying rare variation. Still this approach faces the analytic challenge that the influence of very rare variants can only be evaluated effectively as a group. A further complication is that any given rare variant could have no effect, could increase risk, or could be protective. We propose here the C-alpha test statistic as a novel approach for testing for the presence of this mixture of effects across a set of rare variants. Unlike existing burden tests, C-alpha, by testing the variance rather than the mean, maintains consistent power when the target set contains both risk and protective variants. Through simulations and analysis of case/control data, we demonstrate good power relative to existing methods that assess the burden of rare variants in individuals.
ISSN:1553-7404
1553-7390
1553-7404
DOI:10.1371/journal.pgen.1001322