Related papers: Matrix eQTL: Ultra fast eQTL analysis via large ma…
Genome-wide eQTL mapping explores the relationship between gene expression values and DNA variants to understand genetic causes of human disease. Due to the large number of genes and DNA variants that need to be assessed simultaneously,…
Expression quantitative trait loci (eQTL) analysis identifies genetic markers associated with the expression of a gene. Most existing eQTL analyses and methods investigate association in a single, readily available tissue, such as blood.…
Mapping expression Quantitative Trait Loci (eQTLs) represents a powerful and widely-adopted approach to identifying putative regulatory variants and linking them to specific genes. Up to now eQTL studies have been conducted in a relatively…
Transcriptome-wide association studies based on genetically predicted gene expression have the potential to identify novel regions associated with various complex traits. It has been shown that incorporating expression quantitative trait…
An expression quantitative trait locus (eQTL) is a chromosomal region where genetic variants are associated with the expression levels of certain genes that can be both nearby or distant. The identifications of eQTLs for different tissues,…
Expression quantitative trait loci (eQTL) analyses, which identify genetic markers associated with the expression of a gene, are an important tool in the understanding of diseases in human and other populations. While most eQTL studies to…
Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression…
Genetic variants in cis-regulatory elements or trans-acting regulators commonly influence the quantity and spatiotemporal distribution of gene transcription. Recent interest in expression quantitative trait locus (eQTL) mapping has…
The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression…
Expression quantitative trait loci (eQTL) mapping constitutes a challenging problem due to, among other reasons, the high-dimensional multivariate nature of gene-expression traits. Next to the expression heterogeneity produced by…
The discovery of genomic polymorphisms influencing gene expression (also known as expression quantitative trait loci or eQTLs) can be formulated as a sparse Bayesian multivariate/multiple regression problem. An important aspect in the…
Studies of the genetic loci that contribute to variation in gene expression frequently identify loci with broad effect on gene expression: expression quantitative trait locus (eQTL) hotspots. We describe a set of exploratory graphical…
Most statistical methods for QTL mapping focus on a single phenotype. However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including…
Genetic variation affecting gene regulation is a central driver of phenotypic differences between individuals and can be used to uncover how biological processes are organized in a cell. Although detecting cis-eQTLs is now routine,…
Pedigree GWAS (Option 29) in the current version of the Mendel software is an optimized subroutine for performing large scale genome-wide QTL analysis. This analysis (a) works for random sample data, pedigree data, or a mix of both, (b) is…
We consider the problem of learning a high-dimensional multi-task regression model, under sparsity constraints induced by presence of grouping structures on the input covariates and on the output predictors. This problem is primarily…
Graph network science is becoming increasingly popular, notably in big-data perspective where understanding individual entities for individual functional roles is complex and time consuming. It is likely when a set of genes are regulated by…
In recent years, functional genomics approaches combining genetic information with bulk RNA-sequencing data have identified the downstream expression effects of disease-associated genetic risk factors through so-called expression…
Regions in the genome that affect complex traits, quantitative trait loci (QTL), can be identified using statistical analysis of genetic and phenotypic data. When restricted maximum-likelihood (REML) models are used, the mapping procedure…
In a mouse intercross with more than 500 animals and genome-wide gene expression data on six tissues, we identified a high proportion (18%) of sample mix-ups in the genotype data. Local expression quantitative trait loci (eQTL; genetic loci…