Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data
Joint Authors
Tian, Yi
Ma, Li
Cai, Xiaohong
Zhu, Jiayan
Source
International Journal of Genomics
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-07
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Simultaneous testing of multiple genetic variants for association is widely recognized as a valuable complementary approach to single-marker tests.
As such, principal component regression (PCR) has been found to have competitive power.
We focus on exploring a robust test for an unknown genetic mode of all SNPs, an unknown Hardy-Weinberg equilibrium (HWE) in a population, and a large number of all SNPs.
First, we propose a new global test by means of the use of codominant codes for all markers and PCR.
The new global test is built on an empirical Bayes-type score statistic for testing marginal associations with each single marker.
The new global test gains power by robustly exploiting the Hardy-Weinberg equilibrium in the control population and effectively using linkage disequilibrium among test markers.
The new global test reduces to PCR when the genotype for each marker is coded as the number of minor alleles.
This connection lends insight into the power of the new global test relative to PCR and some other popular multimarker test methods.
Second, we propose a robust test method based on the new global test and the ordinary PCR test built on a prospective score statistic for testing marginal associations with each single marker when the genotype for each marker is coded as the number of minor alleles by taking the minimum p value of these two tests.
Finally, through extensive simulation studies and analysis of the association between pancreatic cancer and some genes of interest, we show that the proposed robust test method has desirable power and can often identify association signals that may be missed by existing methods.
American Psychological Association (APA)
Tian, Yi& Ma, Li& Cai, Xiaohong& Zhu, Jiayan. 2020. Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data. International Journal of Genomics،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1171249
Modern Language Association (MLA)
Tian, Yi…[et al.]. Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data. International Journal of Genomics No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1171249
American Medical Association (AMA)
Tian, Yi& Ma, Li& Cai, Xiaohong& Zhu, Jiayan. Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data. International Journal of Genomics. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1171249
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1171249