A genome-wide association study (GWAS) was conducted to examine expression quantitative trait loci (eQTLs) for histone genes. We examined common eQTLs for multiple histone genes in 373 European lymphoblastoid cell lines (LCLs). A linear regression model was employed to identify single-nucleotide polymorphisms (SNPs) associated with expression of the histone genes, and the number of eQTLs was de...

Over 14 common single nucleotide polymorphisms (SNP) have been consistently identified from genome-wide association studies (GWAS) as associated with glioma risk in European background. The extent to which and how these genetic variants can improve the prediction of glioma risk has was not been investigated. In this study, we employed three independent case-control datasets in Chinese populatio...

BACKGROUND Correcting for the potential effects of population stratification is an important issue in genome wide association studies (GWAS) of complex traits. Principal component analysis (PCA) of the genetic structure of the population under study with subsequent incorporation of the first several principal components (PCs) in the GWAS regression model is often used for this purpose. PROBLE...

Genome-wide association studies have previously identified 23 genetic loci associated with circulating fibrinogen concentration. These studies used HapMap imputation and did not examine the X-chromosome. 1000 Genomes imputation provides better coverage of uncommon variants, and includes indels. We conducted a genome-wide association analysis of 34 studies imputed to the 1000 Genomes Project ref...

High-dimensional datasets with large amounts of redundant information are nowadays available for hypothesis-free exploration of scientific questions. A particular case is genome-wide association analysis, where variations in the genome are searched for effects on disease or other traits. Bayesian variable selection has been demonstrated as a possible analysis approach, which can account for the...

A recent genome-wide association study reported five loci for which there was strong, but sub-genome-wide significant evidence for association with multiple sclerosis risk. The aim of this study was to evaluate the role of these potential risk loci in a large and independent data set of ≈ 20,000 subjects. We tested five single nucleotide polymorphisms rs228614 (MANBA), rs630923 (CXCR5), rs27441...

BACKGROUND Genome wide association studies are now widely used in the livestock sector to estimate the association among single nucleotide polymorphisms (SNPs) distributed across the whole genome and one or more trait. As computational power increases, the use of machine learning techniques to analyze large genome wide datasets becomes possible. METHODS The objective of this study was to iden...

Whole genome sequencing (WGS) remains prohibitively expensive, which has encouraged the development of methods to impute WGS data into nonsequenced individuals using a framework of single nucleotide polymorphisms genotyped for genome-wide association studies (GWAS). Although successful methods have been developed for cohorts of unrelated individuals, current imputation methods in related indivi...

When planning resequencing studies for complex diseases, previous association and linkage studies can constrain the range of plausible genetic models for a given locus. Here, we explore the combinations of causal risk allele frequency (RAFC ) and genotype relative risk (GRRC ) consistent with no or limited evidence for affected sibling pair (ASP) linkage and strong evidence for case-control ass...

Colorectal cancer (CRC) is one of the most common cancers worldwide with a peak of incidence in industrialised countries. It is a complex disease related to environmental and genetic risk factors. Low-penetrance genetic variations contribute significantly to sporadic and familial form of CRC. Genome-wide association studies (GWAS) have uncovered numerous robust associations between common varia...