Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Epistasis Analysis01:09

Epistasis Analysis

4.9K
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...
4.9K
Epistasis01:39

Epistasis

46.6K
In addition to multiple alleles at the same locus influencing traits, numerous genes or alleles at different locations may interact and influence phenotypes in a phenomenon called epistasis. For example, rabbit fur can be black or brown depending on whether the animal is homozygous dominant or heterozygous at a TYRP1 locus. However, if the rabbit is also homozygous recessive at a locus on the tyrosinase gene (TYR), it will have an unshaded coat that appears white, regardless of its TYRP1...
46.6K
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

72.0K
Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
72.0K
Heritability01:06

Heritability

195
Heritability is a statistical concept that measures the degree to which genetic differences among individuals contribute to trait variations within a population. It is a fundamental idea in genetics, often prone to misinterpretation. Heritability is expressed as a percentage, reflecting the proportion of variation in a specific trait across a population that can be linked to genetic differences. However, it's important to understand that heritability does not determine how "genetic"...
195
Chi-square Analysis02:46

Chi-square Analysis

38.2K
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...
38.2K
Probability Laws01:49

Probability Laws

40.7K
Overview
40.7K

You might also read

Related Articles

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

Sort by
Same author

Decoding the causal drivers of spatial cellular topology.

iScience·2026
Same author

Spatial Mapping of the Precancer-to-Cancer Transition in Breast and Prostate.

Cancer discovery·2026
Same author

LAML-Pro: Joint Maximum Likelihood Inference of Cell Genotypes and Cell Lineage Trees.

bioRxiv : the preprint server for biology·2026
Same author

Multimodal spatial alignment and morphology mapping with MOSAICField.

bioRxiv : the preprint server for biology·2026
Same author

Genomic evolution of pancreatic cancer at single-cell resolution.

Nature genetics·2026
Same author

Riemannian Metric Learning for Alignment of Spatial Multiomics.

bioRxiv : the preprint server for biology·2025
Same journal

Layered social competition coordinates reproductive hierarchy formation in ants.

bioRxiv : the preprint server for biology·2026
Same journal

Combination epigenetic-targeted therapy increases the immunogenicity of poorly immunogenic sarcomas.

bioRxiv : the preprint server for biology·2026
Same journal

Loss of LanC-like proteins delays post-injury regeneration of aging skeletal muscles.

bioRxiv : the preprint server for biology·2026
Same journal

Integrative Transfer Network: Deep Transfer Learning Across Populations and Prediction Targets.

bioRxiv : the preprint server for biology·2026
Same journal

Confidence-supported label-free metabolic imaging with FPhaS phase autofluorescence microscopy.

bioRxiv : the preprint server for biology·2026
Same journal

Sequence-encoded autoinhibition couples mRNA decapping activity to phase separation.

bioRxiv : the preprint server for biology·2026
See all related articles

Related Experiment Video

Updated: Jun 18, 2025

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

22.9K

Quantifying higher-order epistasis: beware the chimera.

Uthsav Chitra, Brian J Arnold, Benjamin J Raphael

    Biorxiv : the Preprint Server for Biology
    |July 29, 2024
    PubMed
    Summary
    This summary is machine-generated.

    The chimeric epistasis formula incorrectly identifies the sign of higher-order interactions. Using multiplicative or additive epistasis formulas provides more accurate biological interpretations of genetic and protein data. This corrects findings in yeast gene networks and drug interactions.

    More Related Videos

    Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
    07:34

    Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

    Published on: August 22, 2018

    8.2K
    Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
    09:37

    Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

    Published on: August 15, 2019

    9.7K

    Related Experiment Videos

    Last Updated: Jun 18, 2025

    An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
    10:17

    An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

    Published on: November 3, 2010

    22.9K
    Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
    07:34

    Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

    Published on: August 22, 2018

    8.2K
    Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
    09:37

    Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

    Published on: August 15, 2019

    9.7K

    Area of Science:

    • Genetics and Evolutionary Biology
    • Bioinformatics and Computational Biology
    • Molecular and Systems Biology

    Background:

    • Epistasis, the interaction between alleles at different genetic loci, is crucial for understanding biological complexity, protein evolution, and genetic interactions.
    • Quantifying epistasis typically involves calculating deviations from additive or multiplicative fitness models, but existing formulas are not always equivalent.
    • A widely used 'chimeric' formula mixes multiplicative and additive scales, potentially leading to misinterpretations, especially for higher-order interactions.

    Purpose of the Study:

    • To critically evaluate the mathematical soundness of different epistasis quantification formulas, particularly the 'chimeric' formula.
    • To derive fundamental connections between epistasis formulas and the multivariate Bernoulli distribution for accurate modeling.
    • To re-evaluate biological data using corrected epistasis measures and assess the impact on biological interpretations.

    Main Methods:

    • Mathematical derivation of relationships between epistasis formulas and the multivariate Bernoulli distribution.
    • Comparative analysis of epistasis magnitudes and signs generated by chimeric, multiplicative, and additive formulas for pairwise and higher-order interactions.
    • Re-analysis of existing biological datasets, including yeast gene knockouts, bacterial drug interactions, and protein deep mutational scanning (DMS) data.

    Main Results:

    • The chimeric formula can yield different magnitudes and signs of epistasis compared to the multiplicative formula for higher-order interactions, leading to misclassification of synergistic vs. antagonistic effects.
    • The multiplicative and additive epistasis formulas are mathematically more robust than the chimeric formula.
    • Re-analysis of biological data revealed that 10-60% of higher-order interactions change sign when using appropriate multiplicative or additive formulas, significantly altering biological conclusions.

    Conclusions:

    • The chimeric epistasis formula introduces significant mathematical inconsistencies that lead to erroneous biological interpretations.
    • Corrected analysis using multiplicative or additive epistasis formulas reveals substantial differences in understanding gene function, drug interactions, and protein evolution.
    • In yeast, the multiplicative formula identified nearly 500 additional negative three-way interactions, expanding the trigenic network by 25% and highlighting the importance of accurate epistasis measurement.