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Genome-Wide Association Study

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Powerful Tests for Multi-Marker Association Analysis Using Ensemble Learning.

PloS one
Multi-marker approaches have received a lot of attention recently in genome wide association studies and can enhance power to detect new associations under certain conditions. Gene-, gene-set- and pathway-based association tests are increasingly bein...

Genome-Wide Detection and Analysis of Multifunctional Genes.

PLoS computational biology
Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular...

Sparse Markov chain-based semi-supervised multi-instance multi-label method for protein function prediction.

Journal of bioinformatics and computational biology
Automated assignment of protein function has received considerable attention in recent years for genome-wide study. With the rapid accumulation of genome sequencing data produced by high-throughput experimental techniques, the process of manually pre...

Knowledge-based analysis of genetic associations of rheumatoid arthritis to inform studies searching for pleiotropic genes: a literature review and network analysis.

Arthritis research & therapy
INTRODUCTION: Pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. Gene variants directly affect the normal processes of a series of physiological and biochemical reactions, and therefore cause a variety of diseases...

A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype.

BioMed research international
Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic vari...

Model-Based Multifactor Dimensionality Reduction for Rare Variant Association Analysis.

Human heredity
Genome-wide association studies have revealed a vast amount of common loci associated to human complex diseases. Still, a large proportion of heritability remains unexplained. The extent to which rare genetic variants (RVs) are able to explain a rele...

Identification of active transcriptional regulatory elements from GRO-seq data.

Nature methods
Modifications to the global run-on and sequencing (GRO-seq) protocol that enrich for 5'-capped RNAs can be used to reveal active transcriptional regulatory elements (TREs) with high accuracy. Here, we introduce discriminative regulatory-element detec...

Aber-OWL: a framework for ontology-based data access in biology.

BMC bioinformatics
BACKGROUND: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within t...

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

BMC genomics
BACKGROUND: Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large ...