Modifiers and Subtype-Specific Analyses in Whole-Genome Association Studies: A Likelihood Framework | Zendy

Susan J. Lee | Zendy; Sarah E. Bergen | Zendy; Roy H. Perlis | Zendy; Patrick F. Sullivan | Zendy; Pamela Sklar | Zendy; Jordan W. Smoller | Zendy; Shaun Purcell | Zendy

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Modifiers and Subtype-Specific Analyses in Whole-Genome Association Studies: A Likelihood Framework

Author(s) -

Susan J. Lee,

Sarah E. Bergen,

Roy H. Perlis,

Patrick F. Sullivan,

Pamela Sklar,

Jordan W. Smoller,

Shaun Purcell

Publication year - 2011

Publication title -

human heredity

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.423

H-Index - 62

eISSN - 1423-0062

pISSN - 0001-5652

DOI - 10.1159/000327158

Subject(s) - genetic association , genome wide association study , selection (genetic algorithm) , association (psychology) , statistical power , disease , genetic model , computational biology , biology , type i and type ii errors , multiple comparisons problem , genetics , computer science , statistics , single nucleotide polymorphism , mathematics , medicine , machine learning , psychology , gene , genotype , psychotherapist

We propose new statistical methods for analyzing genetic case/control association data in which cases can be further classified into subtypes, for example, based on clinical features. The primary utility of our work is the ability to distinguish between subtype-specific and modifier effects of genetic variants within a single testing framework.

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