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Genetic association studies have been a popular approach for assessing the association between common Single Nucleotide Polymorphisms (SNPs) and complex diseases. However, other genomic data involved in the mechanism from SNPs to disease,…

Applications · Statistics 2014-04-28 Yen-Tsung Huang , Tyler J. VanderWeele , Xihong Lin

Genetic association analyses often involve data from multiple potentially-heterogeneous subgroups. The expected amount of heterogeneity can vary from modest (e.g., a typical meta-analysis) to large (e.g., a strong gene--environment…

Methodology · Statistics 2014-04-15 Xiaoquan Wen , Matthew Stephens

Genetic association studies, in particular the genome-wide association study design, have provided a wealth of novel insights into the aetiology of a wide range of human diseases and traits. The next challenge consists of understanding the…

A large amount of research has been devoted to the detection and investigation of epistatic interactions in genome-wide association studies (GWASs). Most of the literature focuses on low-order interactions between single-nucleotide…

Applications · Statistics 2017-02-17 Virginie Stanislas , Cyril Dalmasso , Christophe Ambroise

Modeling relations between individuals is a classical question in social sciences and clustering individuals according to the observed patterns of interactions allows to uncover a latent structure in the data. Stochastic block model (SBM)…

Methodology · Statistics 2015-01-27 Pierre Barbillon , Sophie Donnet , Emmanuel Lazega , Avner Bar-Hen

Recent advances of information technology in biomedical sciences and other applied areas have created numerous large diverse data sets with a high dimensional feature space, which provide us a tremendous amount of information and new…

Applications · Statistics 2008-12-18 Yulan Liang , Arpad Kelemen

We study the correlation of the occurrence of coronary heart disease (CHD) with the presence of the single-nucleotide polymorphism (SNP) at the -308 position of the tumor necrosis factor alpha (TNF-$\alpha$) gene. We also consider the…

Quantitative Methods · Quantitative Biology 2011-05-06 Ekaterini Vourvouhaki , C. Sofia Carvalho

High-dimensional variable selection has emerged as one of the prevailing statistical challenges in the big data revolution. Many variable selection methods have been adapted for identifying single nucleotide polymorphisms (SNPs) linked to…

Methodology · Statistics 2024-08-21 Justin J. Van Ee , Diana Gamba , Jesse R. Lasky , Megan L. Vahsen , Mevin B. Hooten

After the completion of human genome sequence was anounced, it is evident that interpretation of DNA sequences is an immediate task to work on. For understanding their signals, improvement of present sequence analysis tools and developing…

Computational Complexity · Computer Science 2007-05-23 Gene Kim , MyungHo Kim

Methods to effectively detect multi-locus genetic association are becoming increasingly relevant in the genetic dissection of complex trait in humans. Current approaches typically consider a limited number of hypotheses, most of which are…

Genomics · Quantitative Biology 2007-05-23 Zhong Li , Aris Floratos , David Wang , Andrea Califano

In this paper, association results from genome-wide association studies (GWAS) are combined with a deep learning framework to test the predictive capacity of statistically significant single nucleotide polymorphism (SNPs) associated with…

Computers and Society · Computer Science 2018-08-27 Casimiro Adays Curbelo Montañez , Paul Fergus , Almudena Curbelo Montañez , Carl Chalmers

This paper describes a Bayesian statistical method for determining the genetic basis of a complex genetic trait. The method uses a sample of unrelated individuals classified into two groups, for example cases and controls. Each group is…

Genomics · Quantitative Biology 2008-02-21 Toby Johnson

Genome-wide association studies (GWAS) have successfully identified over two hundred thousand genotype-trait associations. Yet some challenges remain. First, complex traits are often associated with many single nucleotide polymorphisms…

Methodology · Statistics 2023-02-07 Aastha Khatiwada , Ayse Selen Yilmaz , Bethany J. Wolf , Maciej Pietrzak , Dongjun Chung

Disease-gene association through Genome-wide association study (GWAS) is an arduous task for researchers. Investigating single nucleotide polymorphisms (SNPs) that correlate with specific diseases needs statistical analysis of associations.…

Quantitative Methods · Quantitative Biology 2020-12-21 Sezin Kircali Ata , Min Wu , Yuan Fang , Le Ou-Yang , Chee Keong Kwoh , Xiao-Li Li

Single nucleotide polymorphisms (SNPs) are variations at specific locations in DNA. Sequence responsible for marking genes associated with diseases or tracking inherited diseases within The family. These variations in the Rb1 gene can cause…

Other Quantitative Biology · Quantitative Biology 2023-08-10 Anum Munir

A computationally simple genome-wide association study (GWAS) algorithm for estimating the main and epistatic effects of markers or single nucleotide polymorphisms (SNPs) is proposed. It is based on the intuitive assumption that changes of…

Quantitative Methods · Quantitative Biology 2017-08-08 Lev V. Utkin , Irina L. Utkina

The joint modeling of longitudinal and time-to-event data is an important tool of growing popularity to gain insights into the association between a biomarker and an event process. We develop a general framework of flexible additive joint…

Genome Wide Association Studies (GWAS) and eQTL analyses have produced a large and growing number of genetic associations linked to a wide range of human phenotypes. As of 2013, there were more than 11,000 SNPs associated with a trait as…

Genomics · Quantitative Biology 2016-09-28 John Platig , Peter Castaldi , Dawn DeMeo , John Quackenbush

Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using…

Motivation: Genome-Wide Association Studies (GWAS) seek to identify causal genomic variants associated with rare human diseases. The classical statistical approach for detecting these variants is based on univariate hypothesis testing, with…

Methodology · Statistics 2018-10-22 Florent Guinot , Marie Szafranski , Christophe Ambroise , Franck Samson