| dc.identifier.uri | http://hdl.handle.net/11401/77676 | |
| dc.description.sponsorship | This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. | en_US |
| dc.format | Monograph | |
| dc.format.medium | Electronic Resource | en_US |
| dc.language.iso | en_US | |
| dc.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dc.type | Dissertation | |
| dcterms.abstract | In genome-wide association studies (GWAS), the efficient incorporation of linkage disequilibria (LD) among dense-typed linked genetic variants into analysis to improve the association power is critical yet challenging problem. Functional linear models (FLM), which impose a smoothing structure on the coefficients of correlated covariates, are advantageous in genetic mapping of multiple variants with high LD. Here we propose a novel constrained FLM (cFLM) framework to perform simultaneous association tests on a block of linked SNPs with various traits, including continuous, binary and zero-inflated count phenotypes. The new cFLM applies a set of inequality constraints on the FLM to ensure model identifiability under different genetic codings. The method is implemented via B-splines, with an augmented Lagrangian algorithm is employed for parameter estimation. For hypotheses testing, a test statistic that accounts for the model constraints has been derived, following a mixture of chi-square distributions. Simulation results show that cFLM is effective in identifying causal loci and gene clusters compared to several competing methods based on single markers and SKAT-C. We applied the proposed method to analyze the COGEND data and a large-scale GWAS data on dental caries risk. | |
| dcterms.available | 2017-09-20T16:53:18Z | |
| dcterms.contributor | Zhu, Wei | en_US |
| dcterms.contributor | Wu, Song | en_US |
| dcterms.contributor | Yang, Jie | en_US |
| dcterms.contributor | Bahou, Wadie. | en_US |
| dcterms.creator | Huang, Jiayu | |
| dcterms.dateAccepted | 2017-09-20T16:53:18Z | |
| dcterms.dateSubmitted | 2017-09-20T16:53:18Z | |
| dcterms.description | Department of Applied Mathematics and Statistics. | en_US |
| dcterms.extent | 117 pg. | en_US |
| dcterms.format | Monograph | |
| dcterms.format | Application/PDF | en_US |
| dcterms.identifier | http://hdl.handle.net/11401/77676 | |
| dcterms.issued | 2016-12-01 | |
| dcterms.language | en_US | |
| dcterms.provenance | Made available in DSpace on 2017-09-20T16:53:18Z (GMT). No. of bitstreams: 1
Huang_grad.sunysb_0771E_12691.pdf: 5447699 bytes, checksum: e926cf721e6b81ba9022a4877f8dc638 (MD5)
Previous issue date: 1 | en |
| dcterms.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dcterms.subject | Statistics | |
| dcterms.title | Constrained Functional Linear Model for Multi-loci Genetic Mapping | |
| dcterms.type | Dissertation | |
