scholarly journals Corrigendum of 'High throughput analysis of epistasis in genome-wide association studies with BiForce'

2013 ◽  
Vol 29 (20) ◽  
pp. 2667-2668
Author(s):  
A. Gyenesei ◽  
C. A. M. Semple ◽  
C. S. Haley ◽  
W.-H. Wei
Keyword(s):  
High Throughput ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Genome Wide

scholarly journals High-throughput analysis of epistasis in genome-wide association studies with BiForce

2012 ◽  
Vol 28 (15) ◽  
pp. 1957-1964 ◽  
Author(s):  
Attila Gyenesei ◽  
Jonathan Moody ◽  
Colin A.M. Semple ◽  
Chris S. Haley ◽  
Wen-Hua Wei
Keyword(s):  
High Throughput ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Genome Wide

scholarly journals 026.Endometriosis — linkage, positional cloning and genome wide association

2004 ◽  
Vol 16 (9) ◽  
pp. 26
Author(s):  
G. W. Montgomery ◽  
J. Wicks ◽  
Z. Z. Zhao ◽  
D. R. Nyholt ◽  
N. G. Martin ◽  
...  
Keyword(s):  
High Throughput ◽  
Positional Cloning ◽  
Complex Disease ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Single Experiment ◽  
Priority List ◽  
Genome Wide

Endometriosis is a complex disease which affects up to 10% of women in their reproductive years. Common symptoms include severe dysmenorrhea and pelvic pain. The disease is associated with subfertility and some malignancies. Genetic and environmental factors both influence endometriosis. The aim of our studies is to identify genetic variation contributing to endometriosis and define pathways leading to disease. We recruited a large cohort of affected sister pair (ASP) families where two sisters have had surgically confirmed disease and conducted a 10�cM genome scan. The results of the linkage analysis identified one chromosomal region with significant linkage and one region of suggestive linkage. The regions implicated by these studies are generally of the order of 20–30�cM and include several hundred genes. Locating the gene or genes contributing to disease within the region is a challenging task. The best approach to the problem is association studies using a high density of SNP markers. The recent development of human SNP maps and high throughput SNP genotyping platforms makes this task easier. We have developed high throughput SNP typing at QIMR using the Sequenom MassARRAY platform. The method allows multiple SNP assays to be genotyped on the same sample in a single experiment. Throughput and genotyping costs depend critically on this level of multiplexing and we routinely genotype 6–8 SNPs in a single assay. We are using bioinformatics and functional approaches to develop a priority list of genes to screen early in the project. SNP markers in these genes are being genotyped using the MassARRAY platform to search for genes contributing to endometriosis. In the future, genome wide association studies with our families may locate additional genes contributing to endometriosis.

scholarly journals Prostate cancer genomics by high-throughput technologies: genome-wide association study and sequencing analysis

2013 ◽  
Vol 20 (4) ◽  
pp. R171-R181 ◽  
Author(s):  
Hidewaki Nakagawa
Keyword(s):  
Prostate Cancer ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Genome Wide Association Study ◽  
Cancer Genomics ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Sequencing Analysis ◽  
Genome Wide

Prostate cancer (PC) is the most common malignancy in males. It is evident that genetic factors at both germline and somatic levels play critical roles in prostate carcinogenesis. Recently, genome-wide association studies (GWAS) by high-throughput genotyping technology have identified more than 70 germline variants of various genes or chromosome loci that are significantly associated with PC susceptibility. They include multiple 8q24 loci, prostate-specific genes, and metabolism-related genes. Somatic alterations in PC genomes have been explored by high-throughput sequencing technologies such as whole-genome sequencing and RNA sequencing, which have identified a variety of androgen-responsive events and fusion transcripts represented by E26 transformation-specific (ETS) gene fusions. Recent innovations in high-throughput genomic technologies have enabled us to analyze PC genomics more comprehensively, more precisely, and on a larger scale in multiple ethnic groups to increase our understanding of PC genomics and biology in germline and somatic studies, which can ultimately lead to personalized medicine for PC diagnosis, prevention, and therapy. However, these data indicate that the PC genome is more complex and heterogeneous than we expected from GWAS and sequencing analyses.

scholarly journals A high-throughput SNP typing system for genome-wide association studies

2001 ◽  
Vol 46 (8) ◽  
pp. 471-477 ◽  
Author(s):  
Y. Ohnishi ◽  
T. Tanaka ◽  
K. Ozaki ◽  
R. Yamada ◽  
H. Suzuki ◽  
...  
Keyword(s):  
High Throughput ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Snp Typing ◽  
Genome Wide ◽  
Typing System

scholarly journals BiForce Toolbox: powerful high-throughput computational analysis of gene-gene interactions in genome-wide association studies

2012 ◽  
Vol 40 (W1) ◽  
pp. W628-W632 ◽  
Author(s):  
A. Gyenesei ◽  
J. Moody ◽  
A. Laiho ◽  
C. A. M. Semple ◽  
C. S. Haley ◽  
...  
Keyword(s):  
High Throughput ◽  
Computational Analysis ◽  
Association Studies ◽  
Genome Wide Association ◽  
Gene Interactions ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals High-throughput and efficient multilocus genome-wide association study on longitudinal outcomes

2020 ◽  
Vol 36 (10) ◽  
pp. 3004-3010
Author(s):  
Huang Xu ◽  
Xiang Li ◽  
Yaning Yang ◽  
Yi Li ◽  
Jose Pinheiro ◽  
...  
Keyword(s):  
High Throughput ◽  
Association Studies ◽  
Genomic Data ◽  
Genome Wide Association ◽  
Supplementary Information ◽  
High Dimensional ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Multilocus Analysis ◽  
Analytical Approaches

Abstract Motivation With the emerging of high-dimensional genomic data, genetic analysis such as genome-wide association studies (GWAS) have played an important role in identifying disease-related genetic variants and novel treatments. Complex longitudinal phenotypes are commonly collected in medical studies. However, since limited analytical approaches are available for longitudinal traits, these data are often underutilized. In this article, we develop a high-throughput machine learning approach for multilocus GWAS using longitudinal traits by coupling Empirical Bayesian Estimates from mixed-effects modeling with a novel ℓ0-norm algorithm. Results Extensive simulations demonstrated that the proposed approach not only provided accurate selection of single nucleotide polymorphisms (SNPs) with comparable or higher power but also robust control of false positives. More importantly, this novel approach is highly scalable and could be approximately >1000 times faster than recently published approaches, making genome-wide multilocus analysis of longitudinal traits possible. In addition, our proposed approach can simultaneously analyze millions of SNPs if the computer memory allows, thereby potentially allowing a true multilocus analysis for high-dimensional genomic data. With application to the data from Alzheimer's Disease Neuroimaging Initiative, we confirmed that our approach can identify well-known SNPs associated with AD and were much faster than recently published approaches (≥6000 times). Availability and implementation The source code and the testing datasets are available at https://github.com/Myuan2019/EBE_APML0. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Human Genomic Loci Important in Common Infectious Diseases: Role of High-Throughput Sequencing and Genome-Wide Association Studies

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Gerald Mboowa ◽  
Ivan Sserwadda ◽  
Marion Amujal ◽  
Norah Namatovu
Keyword(s):  
Infectious Diseases ◽  
Positive Selection ◽  
High Throughput ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Host Pathogen

HIV/AIDS, tuberculosis (TB), and malaria are 3 major global public health threats that undermine development in many resource-poor settings. Recently, the notion that positive selection during epidemics or longer periods of exposure to common infectious diseases may have had a major effect in modifying the constitution of the human genome is being interrogated at a large scale in many populations around the world. This positive selection from infectious diseases increases power to detect associations in genome-wide association studies (GWASs). High-throughput sequencing (HTS) has transformed both the management of infectious diseases and continues to enable large-scale functional characterization of host resistance/susceptibility alleles and loci; a paradigm shift from single candidate gene studies. Application of genome sequencing technologies and genomics has enabled us to interrogate the host-pathogen interface for improving human health. Human populations are constantly locked in evolutionary arms races with pathogens; therefore, identification of common infectious disease-associated genomic variants/markers is important in therapeutic, vaccine development, and screening susceptible individuals in a population. This review describes a range of host-pathogen genomic loci that have been associated with disease susceptibility and resistant patterns in the era of HTS. We further highlight potential opportunities for these genetic markers.

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