Integrative information theoretic network analysis for genome-wide association study of aspirin exacerbated respiratory disease in Korean population.

Background: Aspirin Exacerbated Respiratory Disease (AERD) is a chronic medical condition that encompasses asthma, nasal polyposis, and hypersensitivity to aspirin and other non-steroidal anti-inflammatory drugs. Several previous studies have shown that part of the genetic effects of the disease may be induced by the interaction of multiple genetic variants. However, heavy computational cost as well as the complexity of the underlying biological mechanism has prevented a thorough investigation of epistatic interactions and thus most previous studies have typically considered only a small number of genetic variants at a time.

A comment on two-locus epistatic interaction models for genome-wide association studies.

Detection of epistatic interactions in genome-wide association studies is a computationally hard problem. Many detection algorithms have been proposed and will continue to be. Most of those algorithms measure their predictive power by running on simulated data many times under various disease models.

Integrative network analysis for survival-associated gene-gene interactions across multiple genomic profiles in ovarian cancer.

Background: Recent advances in high-throughput technology and the emergence of large-scale genomic datasets have enabled detection of genomic features that affect clinical outcomes. Although many previous computational studies have analysed the effect of each single gene or the additive effects of multiple genes on the clinical outcome, less attention has been devoted to the identification of gene-gene interactions of general type that are associated with the clinical outcome. Moreover, the integration of information from multiple molecular profiles adds another challenge to this problem.

Investigating the utility of clinical outcome-guided mutual information network in network-based Cox regression.

Background: Network-based approaches have recently gained considerable popularity in high- dimensional regression settings. For example, the Cox regression model is widely used in expression analysis to predict the survival of patients. However, as the number of genes becomes substantially larger than the number of samples, the traditional Cox or L2-regularized Cox models are still prone to noise and produce unreliable estimations of regression coefficients.

Fast detection of high-order epistatic interactions in genome-wide association studies using information theoretic measure.

There are many algorithms for detecting epistatic interactions in GWAS. However, most of these algorithms are applicable only for detecting two-locus interactions. Some algorithms are designed to detect only two-locus interactions from the beginning.

Association of four-locus gene interaction with aspirin-intolerant asthma in Korean asthmatics.

Introduction: Aspirin-intolerant asthma (AIA), a major clinical presentation of aspirin hypersensitivity, affects 10% of adult asthmatics. The genetic risk factors involved in the susceptibility to AIA have recently been investigated, but multilocus single-nucleotide polymorphisms (SNPs) associated with this susceptibility has not been evaluated.

Methods: We examined 246 asthmatic patients: 94 having aspirin intolerance and 152 having aspirin tolerance.