Abstract
Identification of multifactor gene-gene (GxG) and gene-environment (GxE) interactions underlying complex traits poses one of the great challenges to today’s genetic study. Development of the generalized multifactor dimensionality reduction (GMDR) method provides a practicable solution to problems in detection of interactions. To exploit the opportunities brought by the availability of diverse data, it is in high demand to develop the corresponding GMDR software that can handle a breadth of phenotypes, such as continuous, count, dichotomous, polytomous nominal, ordinal, survival and multivariate, and various kinds of study designs, such as unrelated case-control, family-based and pooled unrelated and family samples, and also allows adjustment for covariates. We developed a versatile GMDR package to implement this serial of GMDR analyses for various scenarios (e.g., unified analysis of unrelated and family samples) and large-scale (e.g., genome-wide) data. This package includes other desirable features such as data management and preprocessing. Permutation testing strategies are also built in to evaluate the threshold or empirical p values. In addition, its performance is scalable to the computational resources. The software is available at http:// www.soph.uab.edu/ssg/software or http://ibi.zju.edu.cn/software.
Keywords: Generalized multifactor dimensionality reduction, Gene-gene interactions, Gene-environment interactions, Complex traits, Unrelated sample, Family sample, Computer software.
Current Genomics
Title:GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environment Interactions Underlying Complex Traits
Volume: 17 Issue: 5
Author(s): Hai-Ming Xu, Li-Feng Xu, Ting-Ting Hou, Lin-Feng Luo, Guo-Bo Chen, Xi-Wei Sun and Xiang-Yang Lou
Affiliation:
Keywords: Generalized multifactor dimensionality reduction, Gene-gene interactions, Gene-environment interactions, Complex traits, Unrelated sample, Family sample, Computer software.
Abstract: Identification of multifactor gene-gene (GxG) and gene-environment (GxE) interactions underlying complex traits poses one of the great challenges to today’s genetic study. Development of the generalized multifactor dimensionality reduction (GMDR) method provides a practicable solution to problems in detection of interactions. To exploit the opportunities brought by the availability of diverse data, it is in high demand to develop the corresponding GMDR software that can handle a breadth of phenotypes, such as continuous, count, dichotomous, polytomous nominal, ordinal, survival and multivariate, and various kinds of study designs, such as unrelated case-control, family-based and pooled unrelated and family samples, and also allows adjustment for covariates. We developed a versatile GMDR package to implement this serial of GMDR analyses for various scenarios (e.g., unified analysis of unrelated and family samples) and large-scale (e.g., genome-wide) data. This package includes other desirable features such as data management and preprocessing. Permutation testing strategies are also built in to evaluate the threshold or empirical p values. In addition, its performance is scalable to the computational resources. The software is available at http:// www.soph.uab.edu/ssg/software or http://ibi.zju.edu.cn/software.
Export Options
About this article
Cite this article as:
Xu Hai-Ming, Xu Li-Feng, Hou Ting-Ting, Luo Lin-Feng, Chen Guo-Bo, Sun Xi-Wei and Lou Xiang-Yang, GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environment Interactions Underlying Complex Traits, Current Genomics 2016; 17 (5) . https://dx.doi.org/10.2174/1389202917666160513102612
DOI https://dx.doi.org/10.2174/1389202917666160513102612 |
Print ISSN 1389-2029 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5488 |
Call for Papers in Thematic Issues
Advanced AI Techniques in Big Genomic Data Analysis
The thematic issue on "Advanced AI Techniques in Big Genomic Data Analysis" aims to explore the cutting-edge methodologies and applications of artificial intelligence (AI) in the realm of genomic research, where vast amounts of data pose both challenges and opportunities. This issue will cover a broad spectrum of AI-driven strategies, ...read more
Advanced Computational Algorithms and Artificial Intelligence in Clinical Pharmacogenomics
In the era of personalized medicine, understanding the relationship between genetics and drug response is crucial. This issue delves into innovative methodologies, leveraging deep computational analysis and artificial intelligence, to enhance the field of Clinical Pharmacogenomics. The interdisciplinary approach harnesses the power of advanced high-throughput genotyping technologies, sophisticated computational analysis, ...read more
Applications of Single-cell Sequencing Technology in Reproductive Medicine
Single cell sequencing (SCS) technology utilizes individual cells' genetic material to sequence their genome, transcriptome, and epigenetics at the molecular level. It offers insights into cell heterogeneity and enables the study of limited biological materials. Since its recognition as a valuable technique in 2011, single cell sequencing has yielded numerous ...read more
Big Data in Cancer Research
Cancer is a significant threat to human life and health, remaining a highly aggressive killer. It is a leading cause of death worldwide and represents a crucial medical issue for humanity. However, in the past decade, the effectiveness of new synthetic anticancer agents has not matched the current clinical speculation. ...read more
Related Journals
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
- Announcements
Related Articles
-
A Descriptive Analysis of Post-Chemotherapy Development of Interstitial Lung Disease Using Spontaneous Reporting Data in Japan
Current Drug Safety Natural Product Gossypol and its Derivatives in Precision Cancer Medicine
Current Medicinal Chemistry A Closer Look to Polyesters: Properties, Synthesis, Characterization, and Particle Drug Delivery Applications
Nanoscience & Nanotechnology-Asia Sphingosine Kinases Signalling in Carcinogenesis
Mini-Reviews in Medicinal Chemistry Nab-Paclitaxel in Metastatic Breast Cancer: Defining the Best Patient Profile
Current Cancer Drug Targets Other Activities
Current Bioactive Compounds Caveolin Involvement and Modulation in Breast Cancer
Mini-Reviews in Medicinal Chemistry Lipoxygenase Inhibitors for Cancer Prevention: Promises and Risks
Current Pharmaceutical Design Identification of Novel Key Targets and Candidate Drugs in Oral Squamous Cell Carcinoma
Current Bioinformatics Functional Food with Some Health Benefits, So Called Superfood: A Review
Current Nutrition & Food Science Circular RNAs and Glioma: Small Molecule with Big Actions
Current Molecular Medicine Erythropoietin: New Horizon in Cardiovascular Medicine
Recent Patents on Cardiovascular Drug Discovery Targeting Heme for the Identification of Cytotoxic Agents
Anti-Cancer Agents in Medicinal Chemistry Pharmacological Properties and Therapeutic Possibilities for Drugs Acting Upon Endocannabinoid Receptors
Current Drug Targets - CNS & Neurological Disorders The Effects of Soy Isoflavones in Postmenopausal Women: Clinical Review
Current Drug Therapy Isolation, Structural Determination, and Evaluation of the Biological Activity of 20(S)-25-methoxyl-dammarane-3β, 12β, 20-triol [20(S)-25-OCH3-PPD], a Novel Natural Product from Panax notoginseng
Medicinal Chemistry Nutrient-By-Genotype Interactions and Personalized Diet: What Can We Learn From Drosophila and Evolutionary Biology?
Current Pharmacogenomics and Personalized Medicine Some Thiazole Derivatives Combined with Different Heterocycles: Cytotoxicity Evaluation and Apoptosis Inducing Studies
Anti-Cancer Agents in Medicinal Chemistry Cytarabine and Ferric Carboxymaltose (Fe+3) Increase Oxidative Damage and Alter Serotonergic Metabolism in Brain
CNS & Neurological Disorders - Drug Targets Acrylamide Induced Toxicity and the Propensity of Phytochemicals in Amelioration: A Review
Central Nervous System Agents in Medicinal Chemistry