Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data
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...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | International Journal of Genomics |
| Online Access: | http://dx.doi.org/10.1155/2020/4708152 |
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| _version_ | 1832566103465787392 |
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| author | Yi Tian Li Ma Xiaohong Cai Jiayan Zhu |
| author_facet | Yi Tian Li Ma Xiaohong Cai Jiayan Zhu |
| author_sort | Yi Tian |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-eb84f64d7c3e4d04845bcb3897e09431 |
| institution | Kabale University |
| issn | 2314-436X 2314-4378 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Genomics |
| spelling | doaj-art-eb84f64d7c3e4d04845bcb3897e094312025-02-03T01:05:09ZengWileyInternational Journal of Genomics2314-436X2314-43782020-01-01202010.1155/2020/47081524708152Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype DataYi Tian0Li Ma1Xiaohong Cai2Jiayan Zhu3School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, ChinaSchool of Information Engineering, Hubei University of Chinese Medicine, Wuhan 430065, ChinaSchool of Information Engineering, Hubei University of Chinese Medicine, Wuhan 430065, ChinaSchool of Information Engineering, Hubei University of Chinese Medicine, Wuhan 430065, ChinaSimultaneous 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.http://dx.doi.org/10.1155/2020/4708152 |
| spellingShingle | Yi Tian Li Ma Xiaohong Cai Jiayan Zhu Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data International Journal of Genomics |
| title | Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data |
| title_full | Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data |
| title_fullStr | Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data |
| title_full_unstemmed | Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data |
| title_short | Statistical Method Based on Bayes-Type Empirical Score Test for Assessing Genetic Association with Multilocus Genotype Data |
| title_sort | statistical method based on bayes type empirical score test for assessing genetic association with multilocus genotype data |
| url | http://dx.doi.org/10.1155/2020/4708152 |
| work_keys_str_mv | AT yitian statisticalmethodbasedonbayestypeempiricalscoretestforassessinggeneticassociationwithmultilocusgenotypedata AT lima statisticalmethodbasedonbayestypeempiricalscoretestforassessinggeneticassociationwithmultilocusgenotypedata AT xiaohongcai statisticalmethodbasedonbayestypeempiricalscoretestforassessinggeneticassociationwithmultilocusgenotypedata AT jiayanzhu statisticalmethodbasedonbayestypeempiricalscoretestforassessinggeneticassociationwithmultilocusgenotypedata |