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Substantial progress has been made in identifying single genetic variants predisposing to common complex diseases. Nonetheless, the genetic etiology of human diseases remains largely unknown. Human complex diseases are likely influenced by…

Methodology · Statistics 2014-05-27 Zihuai He , Min Zhang , Xiaowei Zhan , Qing Lu

Gene expression represents a fundamental interface between genes and environment in the development and ongoing plasticity of the human organism. Individual differences in gene expression are likely to underpin much of human diversity,…

Genomics · Quantitative Biology 2019-05-31 Akram Yazdani , Raul Mendez Giraldez , Ahmad Samiei

Given genetic variations and various phenotypical traits, such as Magnetic Resonance Imaging (MRI) features, we consider two important and related tasks in biomedical research: i)to select genetic and phenotypical markers for disease…

Machine Learning · Computer Science 2013-10-17 Shandian Zhe , Zenglin Xu , Yuan Qi

When searching for gene pathways leading to specific disease outcomes, additional information on gene characteristics is often available that may facilitate to differentiate genes related to the disease from irrelevant background when…

Machine Learning · Statistics 2018-09-10 Yunpeng Zhao , Qing Pan , Chengan Du

Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), the signals identified by association analysis may not have specific pathological relevance to diseases so…

Genomics · Quantitative Biology 2019-07-19 Rong Jiao , Xiangning Chen , Eric Boerwinkle , Momiao Xiong

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed…

Populations and Evolution · Quantitative Biology 2014-08-19 Jeremy J. Berg , Graham Coop

Motivated by the important problem of detecting association between genetic markers and binary traits in genome-wide association studies, we present a novel Bayesian model that establishes a hierarchy between markers and genes by defining…

Applications · Statistics 2016-06-22 Ian Johnston , Timothy Hancock , Hiroshi Mamitsuka , Luis Carvalho

While linear mixed model (LMM) has shown a competitive performance in correcting spurious associations raised by population stratification, family structures, and cryptic relatedness, more challenges are still to be addressed regarding the…

Machine Learning · Computer Science 2023-02-15 Wenting Ye , Xiang Liu , Tianwei Yue , Wenping Wang

We present an approach, called the "Shadow Method," for the identification of disease loci from dense genetic marker maps in complex, potentially incomplete pedigrees. "Shadow" is a simple method based on an analysis of the patterns of…

Genomics · Quantitative Biology 2007-10-31 Gregory Leibon , Daniel Rockmore , Martin Pollak

In modern scientific studies, it is often imperative to determine whether a set of phenotypes is affected by a single factor. If such an influence is identified, it becomes essential to discern whether this effect is contingent upon…

Methodology · Statistics 2024-03-22 Srijan Chattopadhyay , Swapnaneel Bhattacharyya , Sevantee Basu

Network-based computational approaches to predict unknown genes associated with certain diseases are of considerable significance for uncovering the molecular basis of human diseases. In this paper, we proposed a kind of new…

Molecular Networks · Quantitative Biology 2018-11-14 Ke Hu , Jing-Bo Hu , Ju Xiang , Hui-Jia Li , Yan Zhang , Shi Chen , Chen-He Yi

Identifying shared genetic risk factors for multiple measured traits has been of great interest in studying complex disorders. Marlow's (2003) method for detecting shared gene effects on complex traits has been highly influential in the…

Methodology · Statistics 2009-04-16 Summer S. Han , Elena L. Grigorenko , Joseph T. Chang

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

We propose a resampling-based fast variable selection technique for detecting relevant single nucleotide polymorphisms (SNP) in a multi-marker mixed effect model. Due to computational complexity, current practice primarily involves testing…

Applications · Statistics 2025-04-30 Subhabrata Majumdar , Saonli Basu , Matt McGue , Snigdhansu Chatterjee

We propose a method for detecting differential gene expression that exploits the correlation between genes. Our proposal averages the univariate scores of each feature with the scores in correlation neighborhoods. In a number of real and…

Statistics Theory · Mathematics 2007-06-13 Robert Tibshirani , Larry Wasserman

Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single…

Applications · Statistics 2017-03-22 Hélène Ruffieux , Anthony C. Davison , Jörg Hager , Irina Irincheeva

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially…

In the search for genetic factors that are associated with complex heritable human traits, considerable attention is now being focused on rare variants that individually have small effects. In response, numerous recent papers have proposed…

Methodology · Statistics 2014-09-10 Andriy Derkach , Jerry F. Lawless , Lei Sun

Interactions among multiple genes across the genome may contribute to the risks of many complex human diseases. Whole-genome single nucleotide polymorphisms (SNPs) data collected for many thousands of SNP markers from thousands of…

Applications · Statistics 2011-11-28 Yu Zhang , Jing Zhang , Jun S. Liu

Motivation: Modelling methods that find structure in data are necessary with the current large volumes of genomic data, and there have been various efforts to find subsets of genes exhibiting consistent patterns over subsets of treatments.…

Machine Learning · Computer Science 2016-09-15 Kerstin Bunte , Eemeli Leppäaho , Inka Saarinen , Samuel Kaski