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Full-Text Articles in Physical Sciences and Mathematics
Comparing Performance Of Non-Tree-Based And Tree-Based Association Mapping Methods, Katherine L. Thompson, David W. Fardo
Comparing Performance Of Non-Tree-Based And Tree-Based Association Mapping Methods, Katherine L. Thompson, David W. Fardo
Statistics Faculty Publications
A central goal in the biomedical and biological sciences is to link variation in quantitative traits to locations along the genome (single nucleotide polymorphisms). Sequencing technology has rapidly advanced in recent decades, along with the statistical methodology to analyze genetic data. Two classes of association mapping methods exist: those that account for the evolutionary relatedness among individuals, and those that ignore the evolutionary relationships among individuals. While the former methods more fully use implicit information in the data, the latter methods are more flexible in the types of data they can handle. This study presents a comparison of the 2 …
Uncovering Local Trends In Genetic Effects Of Multiple Phenotypes Via Functional Linear Models, Olga A. Vsevolozhskaya, Dmitri V. Zaykin, David A. Barondess, Xiaoren Tong, Sneha Jadhav, Qing Lu
Uncovering Local Trends In Genetic Effects Of Multiple Phenotypes Via Functional Linear Models, Olga A. Vsevolozhskaya, Dmitri V. Zaykin, David A. Barondess, Xiaoren Tong, Sneha Jadhav, Qing Lu
Biostatistics Faculty Publications
Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear …
Aggregated Quantitative Multifactor Dimensionality Reduction, Rebecca E. Crouch
Aggregated Quantitative Multifactor Dimensionality Reduction, Rebecca E. Crouch
Theses and Dissertations--Statistics
We consider the problem of making predictions for quantitative phenotypes based on gene-to-gene interactions among selected Single Nucleotide Polymorphisms (SNPs). Previously, Quantitative Multifactor Dimensionality Reduction (QMDR) has been applied to detect gene-to-gene interactions associated with elevated quantitative phenotypes, by creating a dichotomous predictor from one interaction which has been deemed optimal. We propose an Aggregated Quantitative Multifactor Dimensionality Reduction (AQMDR), which exhaustively considers all k-way interactions among a set of SNPs and replaces the dichotomous predictor from QMDR with a continuous aggregated score. We evaluate this new AQMDR method in a series of simulations for two-way and three-way interactions, …