Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Epistasis Analysis

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...

Genetic Screens

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...

Wald-Wolfowitz Runs Test I

Wald-Wolfowitz Runs Test I

The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...

Chi-square Analysis

Chi-square Analysis

The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...

Complementation Tests

Complementation Tests

A complementation test is a simple cross to identify whether the two mutations are located on the same gene or different genes. It was first performed by Edward Lewis in the 1940s while working on fruit flies. He developed the test to identify the location and arrangement of different mutations on chromosomes.
Organisms heterozygous for different mutations are crossed pairwise in all combinations. If present on different genes, the mutations can complement each other by providing the missing...

Principles of Pharmacogenetics: Types of Genetic Variants

Principles of Pharmacogenetics: Types of Genetic Variants

The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Genes associated with genetic and rare lung diseases and the risk of lung cancer.

BMC cancer·2026

Same author

Evaluating eight smoking metrics for modelling survival in non-small cell lung cancer.

Cancer epidemiology·2026

Same author

Stratifying lung adenocarcinoma risk with multi-ancestry polygenic risk scores in East Asian never-smokers.

Journal of the National Cancer Institute·2025

Same author

Dysregulation of hair-strand-based elemental biodynamics in amyotrophic lateral sclerosis.

EBioMedicine·2025

Same author

Prediction of seizure outcome with presurgical intracarotid amobarbital procedure, mesial temporal sclerosis on MRI, and PET in surgical candidates with temporal lobe epilepsy.

Epileptic disorders : international epilepsy journal with videotape·2025

Same author

Genes associated with genetic and rare lung diseases and the risk of lung cancer.

Research square·2025

Same journal

Interpretable machine learning for Parkinson's disease diagnosis, staging, and biological mechanism exploration: a multicenter analysis.

BioData mining·2026

Same journal

Learning a distance for the clustering of patients with amyotrophic lateral sclerosis.

BioData mining·2026

Same journal

Multi-domain feature fusion with variational mode decomposition and hybrid LightGBM-Logistic Regression for multi-class seizure classification.

BioData mining·2026

Same journal

Large-scale transcriptomic data mining using explainable XGBoost and SHAP reveals shared biomarkers and molecular mechanisms between type-2 diabetes and triple-negative breast cancer for drug repurposing.

BioData mining·2026

Same journal

AVSeg-XAI: Deep learning framework for A/V segmentation with vascular features reveals retinal oculomics as biomarker for cardiovascular disease.

BioData mining·2026

Same journal

Navigating the uncharted: AI-driven advances in protein structure, dynamics, interactions and ligand interactions for understudied families.

BioData mining·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 23, 2026

A Reverse Genetic Approach to Test Functional Redundancy During Embryogenesis

A Reverse Genetic Approach to Test Functional Redundancy During Embryogenesis

Published on: August 11, 2010

Detecting gene-gene interactions using a permutation-based random forest method.

Jing Li¹, James D Malley², Angeline S Andrew³

¹Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, NH USA.

|April 8, 2016

Summary

This summary is machine-generated.

We developed a novel permuted random forest (pRF) method to identify gene-gene interactions, crucial for understanding complex diseases. This approach successfully detected interacting single nucleotide polymorphism (SNP) pairs in simulations and real-world bladder cancer data.

Keywords:

GWAS Machine learning Random forest Scale invariant

More Related Videos

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Published on: February 3, 2013

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Related Experiment Videos

Last Updated: Mar 23, 2026

A Reverse Genetic Approach to Test Functional Redundancy During Embryogenesis

A Reverse Genetic Approach to Test Functional Redundancy During Embryogenesis

Published on: August 11, 2010

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Published on: February 3, 2013

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Area of Science:

Genetics
Bioinformatics
Machine Learning

Background:

Gene-gene interactions are key to understanding disease susceptibility and complex genetic architectures.
Current methods require new approaches for robust interaction detection.

Purpose of the Study:

To develop a permutation-based methodology using random forest (RF) for detecting gene-gene interactions.
To introduce the permuted random forest (pRF) approach for identifying interacting single nucleotide polymorphism (SNP) pairs.

Main Methods:

Utilized a random forest (RF) machine learning model.
Developed a permutation strategy (pRF) to assess the impact of pairwise interactions on model performance.
Constructed permuted random forest networks (PRFN) with SNPs as nodes and interactions as edges.

Main Results:

The pRF methodology demonstrated high success rates in detecting interaction SNP pairs across diverse simulation scenarios.
Applied to bladder cancer datasets, pRF yielded results consistent with established methods like multifactor dimensionality reduction (MDR) and statistical epistasis network (SEN).

Conclusions:

Successfully developed a scale-invariant methodology for detecting pure gene-gene interactions.
The pRF approach shows significant potential for analyzing genetic architectures in a scale-free manner, aiding in the elucidation of complex disease mechanisms.