Kodaman N, Aldrich MC, Smith JR, Signorello LB, Bradley K, Breyer J, Cohen SS, Long J, Cai Q, Giles J, Bush WS, Blot WJ, Matthews CE, Williams SM,. Using genetic data from an obesity candidate gene study of self-reported African Americans and European Americans, we investigated the number of Ancestry Informative Markers (AIMs) and candidate […]
Since publication of the human genome in 2003, geneticists have been interested in risk variant associations to resolve the etiology of traits and complex diseases. The International HapMap Consortium undertook an effort to catalog all common variation across the genome (variants with a minor allele frequency (MAF) of at least 5% in one or more […]
Buchanan CC, Torstenson ES, Bush WS, Ritchie MD,. Since publication of the human genome in 2003, geneticists have been interested in risk variant associations to resolve the etiology of traits and complex diseases. The International HapMap Consortium undertook an effort to catalog all common variation across the genome (variants with a minor allele frequency (MAF) […]
Multiple sclerosis (MS) is a neurodegenerative, autoimmune disease of the central nervous system, and numerous studies have shown that MS has a strong genetic component. Independent studies to identify MS-associated genes have often indicated multiple signals in physically close genomic regions, although by their proximity it is not always clear if these data indicate redundant […]
Zuvich RL, Bush WS, McCauley JL, Beecham AH, De Jager PL, , Ivinson AJ, Compston A, Hafler DA, Hauser SL, Sawcer SJ, Pericak-Vance MA, Barcellos LF, Mortlock DP, Haines JL,. Multiple sclerosis (MS) is a neurodegenerative, autoimmune disease of the central nervous system, and numerous studies have shown that MS has a strong genetic component. […]
Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also increases power to detect weak main effects. We conducted a knowledge-driven […]
Bush WS, McCauley JL, DeJager PL, Dudek SM, Hafler DA, Gibson RA, Matthews PM, Kappos L, Naegelin Y, Polman CH, Hauser SL, Oksenberg J, Haines JL, Ritchie MD, ,. Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of […]
Yaspan BL, Bush WS, Torstenson ES, Ma D, Pericak-Vance MA, Ritchie MD, Sutcliffe JS, Haines JL,. Genome Wide Association Studies (GWAS) are a standard approach for large-scale common variation characterization and for identification of single loci predisposing to disease. However, due to issues of moderate sample sizes and particularly multiple testing correction, many variants of […]
Genome Wide Association Studies (GWAS) are a standard approach for large-scale common variation characterization and for identification of single loci predisposing to disease. However, due to issues of moderate sample sizes and particularly multiple testing correction, many variants of smaller effect size are not detected within a single allele analysis framework. Thus, small main effects […]
Understanding how genetic variants impact the regulation and expression of genes is important for forging mechanistic links between variants and phenotypes in personal genomics studies. In this work, we investigate statistical interactions among variants that alter gene expression and identify 79 genes showing highly significant interaction effects consistent with genetic heterogeneity. Of the 79 genes, […]
Turner SD, Bush WS,. Understanding how genetic variants impact the regulation and expression of genes is important for forging mechanistic links between variants and phenotypes in personal genomics studies. In this work, we investigate statistical interactions among variants that alter gene expression and identify 79 genes showing highly significant interaction effects consistent with genetic heterogeneity. […]
Simulated data is a necessary first step in the evaluation of new analytic methods because in simulated data the true effects are known. To successfully develop novel statistical and computational methods for genetic analysis, it is vital to simulate datasets consisting of single nucleotide polymorphisms (SNPs) spread throughout the genome at a density similar to […]