Ali, Fadhaa, Zhang, Jian (2015) Search for Risk Haplotype Segments with GWAS Data by Use of Finite Mixture Models. Statistics and its interface, 9 (3). pp. 267-280. ISSN 1938-7989. E-ISSN 1938-7997. (doi:10.4310/SII.2016.v9.n3.a2) (KAR id:49031)
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Official URL http://dx.doi.org/10.4310/SII.2016.v9.n3.a2 |
Abstract
The region-based association analysis has been proposed to capture the
involves a list of unphased multiple-locus genotypes with
To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype co-classification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this
false haplotypes which hamper the detection of rare but true
risk genotypes based on a finite mixture model. In Stage 2, we infer risk haplotypes from risk genotypes inferred from the
To estimate the finite mixture model, we propose an EM algorithm with a novel data partition-based initialization.
simulation studies and a real data analysis. Compared to the existing
multiple Z-test procedure, we find that the power of genome-wide association studies can be increased by using the proposed procedure.
Item Type: | Article |
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DOI/Identification number: | 10.4310/SII.2016.v9.n3.a2 |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Jian Zhang |
Date Deposited: | 16 Jun 2015 13:47 UTC |
Last Modified: | 16 Feb 2021 13:25 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/49031 (The current URI for this page, for reference purposes) |
Zhang, Jian: | ![]() |
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