Abstract Background Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Findings Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic ass...
<div><p>Gene co-expression networks comprise one type of valuable biological networks. Many methods ...
Gene co-expression networks comprise one type of valuable biological networks. Many methods and tool...
AbstractIn the past few years massive amounts of data have been generated for genetic analysis. Exis...
Motivation: Collecting millions of genetic variations is feasible with the advanced genotyping techn...
The extent of data in a typical genome-wide association study (GWAS) poses considerable computationa...
It is being increasingly accepted that traditional statistical Single Nucleotide Polymorphism (SNP) ...
A major goal of a Genome Wide Association Study (GWAS) is to find associations between genetic varia...
It is being increasingly accepted that traditional statistical Single Nucleotide Polymorphism (SNP...
Genome-wide association studies (GWAS) are a common approach for systematic discovery of single nucl...
Genome-wide association studies (GWAS) are a common approach for systematic discovery of single nucl...
Genome wide association studies (GWAS) have proven their value, having found hundreds of thousands o...
Motivation: Quantification of the contribution of genetic variation to phenotypic variation for comp...
Abstract. High-throughput genotyping technologies allow the collec-tion of up to a few million genet...
Abstract Detecting epistasis, such as 2-SNP interac-tions, in Genome-Wide Association Studies (GWAS)...
Gene co-expression networks comprise one type of valuable biological networks. Many methods and tool...
<div><p>Gene co-expression networks comprise one type of valuable biological networks. Many methods ...
Gene co-expression networks comprise one type of valuable biological networks. Many methods and tool...
AbstractIn the past few years massive amounts of data have been generated for genetic analysis. Exis...
Motivation: Collecting millions of genetic variations is feasible with the advanced genotyping techn...
The extent of data in a typical genome-wide association study (GWAS) poses considerable computationa...
It is being increasingly accepted that traditional statistical Single Nucleotide Polymorphism (SNP) ...
A major goal of a Genome Wide Association Study (GWAS) is to find associations between genetic varia...
It is being increasingly accepted that traditional statistical Single Nucleotide Polymorphism (SNP...
Genome-wide association studies (GWAS) are a common approach for systematic discovery of single nucl...
Genome-wide association studies (GWAS) are a common approach for systematic discovery of single nucl...
Genome wide association studies (GWAS) have proven their value, having found hundreds of thousands o...
Motivation: Quantification of the contribution of genetic variation to phenotypic variation for comp...
Abstract. High-throughput genotyping technologies allow the collec-tion of up to a few million genet...
Abstract Detecting epistasis, such as 2-SNP interac-tions, in Genome-Wide Association Studies (GWAS)...
Gene co-expression networks comprise one type of valuable biological networks. Many methods and tool...
<div><p>Gene co-expression networks comprise one type of valuable biological networks. Many methods ...
Gene co-expression networks comprise one type of valuable biological networks. Many methods and tool...
AbstractIn the past few years massive amounts of data have been generated for genetic analysis. Exis...