Literature DB >> 17924838

Novel methods for detecting epistasis in pharmacogenomics studies.

Alison A Motsinger1, Marylyn D Ritchie, David M Reif.   

Abstract

The importance of gene-gene and gene-environment interactions in the underlying genetic architecture of common, complex phenotypes is gaining wide recognition in the field of pharmacogenomics. In epidemiological approaches to mapping genetic variants that predict drug response, it is important that researchers investigate potential epistatic interactions. In the current review, we discuss data-mining tools available in genetic epidemiology to detect such interactions and appropriate applications. We survey several classes of novel methods available and present an organized collection of successful applications in the literature. Finally, we provide guidance as to how to incorporate these novel methods into a genetic analysis. The overall goal of this paper is to aid researchers in developing an analysis plan that accounts for gene-gene and gene-environment in their own work.

Mesh:

Year:  2007        PMID: 17924838     DOI: 10.2217/14622416.8.9.1229

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN: 1462-2416            Impact factor:   2.533


  30 in total

Review 1.  Assessing gene-gene interactions in pharmacogenomics.

Authors:  Hsien-Yuan Lane; Guochuan E Tsai; Eugene Lin
Journal:  Mol Diagn Ther       Date:  2012-02-01       Impact factor: 4.074

2.  A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility.

Authors:  Jiang Gui; Angeline S Andrew; Peter Andrews; Heather M Nelson; Karl T Kelsey; Margaret R Karagas; Jason H Moore
Journal:  Ann Hum Genet       Date:  2010-11-22       Impact factor: 1.670

3.  Pharmacogenetics and pharmacovigilance.

Authors:  Robert H Howland
Journal:  Drug Saf       Date:  2009       Impact factor: 5.606

4.  Gene-gene interactions in the NAMPT pathway, plasma visfatin/NAMPT levels, and antihypertensive therapy responsiveness in hypertensive disorders of pregnancy.

Authors:  M R Luizon; A C T Palei; V A Belo; L M Amaral; R Lacchini; G Duarte; R C Cavalli; V C Sandrim; J E Tanus-Santos
Journal:  Pharmacogenomics J       Date:  2016-05-10       Impact factor: 3.550

5.  Statistical Optimization of Pharmacogenomics Association Studies: Key Considerations from Study Design to Analysis.

Authors:  Benjamin J Grady; Marylyn D Ritchie
Journal:  Curr Pharmacogenomics Person Med       Date:  2011-03-01

Review 6.  Novel genetic and epigenetic factors of importance for inter-individual differences in drug disposition, response and toxicity.

Authors:  Volker M Lauschke; Yitian Zhou; Magnus Ingelman-Sundberg
Journal:  Pharmacol Ther       Date:  2019-01-22       Impact factor: 12.310

7.  Enabling personal genomics with an explicit test of epistasis.

Authors:  Casey S Greene; Daniel S Himmelstein; Heather H Nelson; Karl T Kelsey; Scott M Williams; Angeline S Andrew; Margaret R Karagas; Jason H Moore
Journal:  Pac Symp Biocomput       Date:  2010

8.  Bayesian mixture modeling of gene-environment and gene-gene interactions.

Authors:  Jon Wakefield; Frank De Vocht; Rayjean J Hung
Journal:  Genet Epidemiol       Date:  2010-01       Impact factor: 2.135

9.  Detecting purely epistatic multi-locus interactions by an omnibus permutation test on ensembles of two-locus analyses.

Authors:  Waranyu Wongseree; Anunchai Assawamakin; Theera Piroonratana; Saravudh Sinsomros; Chanin Limwongse; Nachol Chaiyaratana
Journal:  BMC Bioinformatics       Date:  2009-09-17       Impact factor: 3.169

Review 10.  Bioinformatics challenges for genome-wide association studies.

Authors:  Jason H Moore; Folkert W Asselbergs; Scott M Williams
Journal:  Bioinformatics       Date:  2010-01-06       Impact factor: 6.937

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