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Multifactor Dimensionality Reduction

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A unified model based multifactor dimensionality reduction framework for detecting gene-gene interactions.

Bioinformatics (Oxford, England)
MOTIVATION: Gene-gene interaction (GGI) is one of the most popular approaches for finding and explaining the missing heritability of common complex traits in genome-wide association studies. The multifactor dimensionality reduction (MDR) method has b...

An empirical fuzzy multifactor dimensionality reduction method for detecting gene-gene interactions.

BMC genomics
BACKGROUND: Detection of gene-gene interaction (GGI) is a key challenge towards solving the problem of missing heritability in genetics. The multifactor dimensionality reduction (MDR) method has been widely studied for detecting GGIs. MDR reduces the...

Identification of microRNA precursors using reduced and hybrid features.

Molecular bioSystems
MicroRNAs (also called miRNAs) are a group of short non-coding RNA molecules. They play a vital role in the gene expression of transcriptional and post-transcriptional processes. However, abnormality of their expression has been observed in cancer, h...

The R-package GenomicTools for multifactor dimensionality reduction and the analysis of (exploratory) Quantitative Trait Loci.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: We introduce the R-package GenomicTools to perform, among others, a Multifactor Dimensionality Reduction (MDR) for the identification of SNP-SNP interactions. The package further provides a new class of tests for an (explor...

Interaction between SELP genetic polymorphisms with inflammatory cytokine interleukin-6 (IL-6) gene variants on cardiovascular disease in Chinese Han population.

Mammalian genome : official journal of the International Mammalian Genome Society
The aim of the study is to investigate the impact of SELP and IL-6 genetic single-nucleotide polymorphisms (SNPs) and its gene-gene interaction on cardiovascular disease (CVD) risk based on Chinese population. A total of 1082 subjects (519 males, 563...

CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies.

Bioinformatics (Oxford, England)
MOTIVATION: Detecting epistatic interactions in genome-wide association studies (GWAS) is a computational challenge. Such huge numbers of single-nucleotide polymorphism (SNP) combinations limit the some of the powerful algorithms to be applied to det...

Using neural networks for reducing the dimensions of single-cell RNA-Seq data.

Nucleic acids research
While only recently developed, the ability to profile expression data in single cells (scRNA-Seq) has already led to several important studies and findings. However, this technology has also raised several new computational challenges. These include ...

Multiobjective differential evolution-based multifactor dimensionality reduction for detecting gene-gene interactions.

Scientific reports
Epistasis within disease-related genes (gene-gene interactions) was determined through contingency table measures based on multifactor dimensionality reduction (MDR) using single-nucleotide polymorphisms (SNPs). Most MDR-based methods use the single ...

A hierarchical clustering method for dimension reduction in joint analysis of multiple phenotypes.

Genetic epidemiology
Genome-wide association studies (GWAS) have become a very effective research tool to identify genetic variants of underlying various complex diseases. In spite of the success of GWAS in identifying thousands of reproducible associations between genet...

Multiobjective multifactor dimensionality reduction to detect SNP-SNP interactions.

Bioinformatics (Oxford, England)
MOTIVATION: Single-nucleotide polymorphism (SNP)-SNP interactions (SSIs) are popular markers for understanding disease susceptibility. Multifactor dimensionality reduction (MDR) can successfully detect considerable SSIs. Currently, MDR-based methods ...