English
Related papers

Related papers: Disentangling Linkage and Population Structure in …

200 papers

To understand how genetic variants in human genomes manifest in phenotypes -- traits like height or diseases like asthma -- geneticists have sequenced and measured hundreds of thousands of individuals. Geneticists use this data to build…

Machine Learning · Computer Science 2025-07-01 Alan N. Amin , Andres Potapczynski , Andrew Gordon Wilson

With the recent advent of high-throughput genotyping techniques, genetic data for genome-wide association studies (GWAS) have become increasingly available, which entails the development of efficient and effective statistical approaches.…

Applications · Statistics 2015-02-04 Jiahan Li , Wei Zhong , Runze Li , Rongling Wu

In genetic association studies, detecting phenotype-genotype association is a primary goal. We assume that the relationship between the data -phenotype, genetic markers and environmental covariates - can be modelled by a generalized linear…

Methodology · Statistics 2020-04-13 K. K. Halle , Ø. Bakke , S. Djurovic , A. Bye , E. Ryeng , U. Wisløff , O. A. Andreassen , M. Langaas

High-dimensional phenotypes hold promise for richer findings in association studies, but testing of several phenotype traits aggravates the grand challenge of association studies, that of multiple testing. Several methods have recently been…

Methodology · Statistics 2013-05-14 Pekka Marttinen , Jussi Gillberg , Aki Havulinna , Jukka Corander , Samuel Kaski

Genome-Wide Association Studies (GWAS) offer an exciting and promising new research avenue for finding genes for complex diseases. Traditional case-control and cohort studies offer many advantages for such designs. Family-based association…

Methodology · Statistics 2010-10-25 Nan M. Laird , Christoph Lange

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…

We introduce a statistical method that can reconstruct nonlinear genetic models (i.e., including epistasis, or gene-gene interactions) from phenotype-genotype (GWAS) data. The computational and data resource requirements are similar to…

Genomics · Quantitative Biology 2015-09-29 Chiu Man Ho , Stephen D. H. Hsu

Genome-wide association studies (GWASs) aim to detect genetic risk factors for complex human diseases by identifying disease-associated single-nucleotide polymorphisms (SNPs). The traditional SNP-wise approach along with multiple testing…

Methodology · Statistics 2019-09-25 Yan Xu , Li Xing , Jessica Su , Xuekui Zhang , Weiliang Qiu

The aetiology of polygenic obesity is multifactorial, which indicates that life-style and environmental factors may influence multiples genes to aggravate this disorder. Several low-risk single nucleotide polymorphisms (SNPs) have been…

Genomics · Quantitative Biology 2018-08-27 Casimiro A. Curbelo Montañez , Paul Fergus , Carl Chalmers , Jade Hind

When testing for the association of a single SNP with a phenotypic response, one usually considers an additive genetic model, assuming that the mean of of the response for the heterozygous state is the average of the means for the two…

Methodology · Statistics 2025-01-07 Dominic Edelmann , Fernando Castro-Prado , Jelle J. Goeman

Identifying mutations of SARS-CoV-2 strains associated with their phenotypic changes is critical for pandemic prediction and prevention. We compared an explainable convolutional neural network (CNN) approach and the traditional genome-wide…

Genomics · Quantitative Biology 2025-01-03 Parisa Hatami , Richard Annan , Luis Urias Miranda , Jane Gorman , Mengjun Xie , Letu Qingge , Hong Qin

Genome-wide association (GWA) constitutes a prominent portion of studies which have been conducted on personalized medicine and pharmacogenomics. Recently, very few methods have been developed for extracting mutation-diseases associations.…

Computation and Language · Computer Science 2020-12-03 Behrouz Bokharaeian , Alberto Diaz

Genome-wide association studies (GWAS) offer new opportunities to identify genetic risk factors for Alzheimer's disease (AD). Recently, collaborative efforts across different institutions emerged that enhance the power of many existing…

Machine Learning · Computer Science 2016-08-26 Qingyang Li , Tao Yang , Liang Zhan , Derrek Paul Hibar , Neda Jahanshad , Yalin Wang , Jieping Ye , Paul M. Thompson , Jie Wang

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

One of the most important challenges in the analysis of high-throughput genetic data is the development of efficient computational methods to identify statistically significant Single Nucleotide Polymorphisms (SNPs). Genome-wide association…

2 Diabetes is a leading worldwide public health concern, and its increasing prevalence has significant health and economic importance in all nations. The condition is a multifactorial disorder with a complex aetiology. The genetic…

Machine Learning · Computer Science 2018-08-30 Basma Abdulaimma , Paul Fergus , Carl Chalmers

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

Heritability is a central parameter in quantitative genetics, both from an evolutionary and a breeding perspective. For plant traits heritability is traditionally estimated by comparing within and between genotype variability. This approach…

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

Many complex disease syndromes such as asthma consist of a large number of highly related, rather than independent, clinical phenotypes, raising a new technical challenge in identifying genetic variations associated simultaneously with…

Machine Learning · Statistics 2008-11-16 Seyoung Kim , Kyung-Ah Sohn , Eric P. Xing