Journal article
Gene‐based genetic association test with adaptive optimal weights
Genetic epidemiology, Vol.42(1), pp.95-103
02/2018
DOI: 10.1002/gepi.22098
PMID: 29178441
Abstract
ABSTRACT
It is well known that using proper weights for genetic variants is crucial in enhancing the power of gene‐ or pathway‐based association tests. To increase the power, we propose a general approach that adaptively selects weights among a class of weight families and apply it to the popular sequencing kernel association test. Through comprehensive simulation studies, we demonstrate that the proposed method can substantially increase power under some conditions. Applications to real data are also presented. This general approach can be extended to all current set‐based rare variant association tests whose performances depend on variant's weight assignment.
Details
- Title: Subtitle
- Gene‐based genetic association test with adaptive optimal weights
- Creators
- Zhongxue Chen - Indiana University BloomingtonYan Lu - University of New MexicoTong Lin - Peking UniversityQingzhong Liu - Sam Houston State UniversityKai Wang - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Genetic epidemiology, Vol.42(1), pp.95-103
- DOI
- 10.1002/gepi.22098
- PMID
- 29178441
- ISSN
- 0741-0395
- eISSN
- 1098-2272
- Number of pages
- 9
- Grant note
- Natural Science Foundation of China (61375051)
- Language
- English
- Date published
- 02/2018
- Academic Unit
- Biostatistics
- Record Identifier
- 9983997484502771
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