Expectile Neural Networks for Genetic Data Analysis of Complex Diseases [PDF]
arXiv, 2020 The genetic etiologies of common diseases are highly complex and heterogeneous. Classic statistical methods, such as linear regression, have successfully identified numerous genetic variants associated with complex diseases. Nonetheless, for most complex diseases, the identified variants only account for a small proportion of heritability.
arxiv
Detection boundary and Higher Criticism approach for rare and weak genetic effects [PDF]
Annals of Applied Statistics 2014, Vol. 8, No. 2, 824-851, 2014 Genome-wide association studies (GWAS) have identified many genetic factors underlying complex human traits. However, these factors have explained only a small fraction of these traits' genetic heritability. It is argued that many more genetic factors remain undiscovered.
arxiv +1 more source
Population Structure and Cryptic Relatedness in Genetic Association Studies [PDF]
, 2009 We review the problem of confounding in genetic association studies, which arises principally because of population structure and cryptic relatedness. Many treatments of the problem consider only a simple ``island'' model of population structure. We take
Astle, William, Balding, David J.
core +4 more sources
Genetics of common polygenic ischaemic stroke: current understanding and future challenges. [PDF]
, 2011 Stroke is the third commonest cause of death and the major cause of adult neurological disability worldwide. While much is known about conventional risk factors such as hypertension, diabetes and incidence of smoking, these environmental factors only ...
Bevan, S, Markus, HS
core +3 more sources
A simulations approach for meta-analysis of genetic association studies based on additive genetic model [PDF]
, 2016 Genetic association studies are becoming an important component of medical research. To cite one instance, pharmacogenomics which is gaining prominence as a useful tool for personalized medicine is heavily reliant on results from genetic association studies.
arxiv +1 more source
Genetic Association Between Insulin Resistance And Total Cholesterol In Type 2 Diabetes Mellitus - A Preliminary Observation [PDF]
, 2005 We investigated the degree of genetic association between insulin resistance (IR) with type 2 diabetes mellitus (DM) and abnormalities in lipid metabolism in 42 patients.
Gunasekara Sudari Wijewickrama +5 more
core +1 more source
Biomolecules & Biomedicine, 2012 Large scale genetic association meta-analyses showed that neurocan (NCAN) gene polymorphism rs1064395 is susceptibility locus for bipolar disorder.
Lilijana Oruč +4 more
doaj +1 more source
Genetic algorithm formulation and tuning with use of test functions [PDF]
arXiv, 2022 This work discusses single-objective constrained genetic algorithm with floating-point, integer, binary and permutation representation. Floating-point genetic algorithm tuning with use of test functions is done and leads to a parameterization with comparatively outstanding performance.
arxiv
Misspecification in mixed-model based association analysis [PDF]
arXiv, 2015 Additive genetic variance in natural populations is commonly estimated using mixed models, in which the covariance of the genetic effects is modeled by a genetic similarity matrix derived from a dense set of markers. An important but usually implicit assumption is that the presence of any non-additive genetic effect only increases the residual variance,
arxiv
Bayesian Neural Networks for Genetic Association Studies of Complex Disease [PDF]
, 2014 Discovering causal genetic variants from large genetic association studies poses many difficult challenges. Assessing which genetic markers are involved in determining trait status is a computationally demanding task, especially in the presence of gene-gene interactions.
arxiv +1 more source