Type
Text
Type
Dissertation
Advisor
Wu, Song | Zhu, Wei | Yang, Jie | Bahou, Wadie.
Date
2016-12-01
Keywords
Statistics
Department
Department of Applied Mathematics and Statistics.
Language
en_US
Source
This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.
Identifier
http://hdl.handle.net/11401/77676
Publisher
The Graduate School, Stony Brook University: Stony Brook, NY.
Format
application/pdf
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. | 117 pages
Recommended Citation
Huang, Jiayu, "Constrained Functional Linear Model for Multi-loci Genetic Mapping" (2016). Stony Brook Theses and Dissertations Collection, 2006-2020 (closed to submissions). 3468.
https://commons.library.stonybrook.edu/stony-brook-theses-and-dissertations-collection/3468