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

Multiple Allele Traits01:49

Multiple Allele Traits

15.2K
15.2K
Multiple Allele Traits01:49

Multiple Allele Traits

39.3K
The Concept of Multiple Allelism
39.3K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

17.2K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
17.2K
Multiple Regression01:25

Multiple Regression

4.4K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
4.4K
Epistasis Analysis01:09

Epistasis Analysis

6.3K
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...
6.3K
Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

7.5K
It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
7.5K

You might also read

Related Articles

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

Sort by
Same author

Life history, climate and biogeography interactively affect worldwide genetic diversity of plant and animal populations.

Nature communications·2021
Same author

Revisiting the phylogeography and demography of European badgers (Meles meles) based on broad sampling, multiple markers and simulations.

Heredity·2014
Same author

Nucleotide sequence and transcriptional analysis of a mitochondrial plasmid from a cytoplasmic male-sterile line of sunflower.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2013
Same author

Optimizing the trade-off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual-based sampling scheme.

Molecular ecology·2013
Same author

Assessment LOPU-IVF in Japanese sika deer (Cervus nippon nippon) and application to Vietnamese sika deer (Cervus nippon pseudaxis) a related subspecies threatened with extinction.

Theriogenology·2012
Same author

Comparative landscape genetic analyses show a Belgian motorway to be a gene flow barrier for red deer (Cervus elaphus), but not wild boars (Sus scrofa).

Molecular ecology·2012

Related Experiment Video

Updated: Apr 19, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

5.1K

Multicollinearity in spatial genetics: separating the wheat from the chaff using commonality analyses.

J G Prunier1, M Colyn, X Legendre

  • 1Institut des Sciences de la Vie, Université catholique de Louvain, Croix du Sud 4, L7.07.14, 1348, Louvain-la-Neuve, Belgium.

Molecular Ecology
|December 16, 2014
PubMed
Summary
This summary is machine-generated.

Commonality analysis (CA) helps spatial genetics by identifying multicollinearity in direct gradient analyses. This method improves interpretation of genetic variation and prevents flawed conservation strategies.

Keywords:
CDPOPcommonality analysislogistic regressionsmultiple regressions on distance matricesspurious correlations

More Related Videos

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.9K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.5K

Related Experiment Videos

Last Updated: Apr 19, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

5.1K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.9K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.5K

Area of Science:

  • Ecology and Evolutionary Biology
  • Genetics
  • Spatial Analysis

Background:

  • Direct gradient analyses are crucial for understanding genetic variation in wildlife.
  • Multicollinearity in explanatory variables poses a significant challenge to interpreting these analyses accurately.
  • Inaccurate interpretations risk misdirected research and ineffective conservation efforts.

Purpose of the Study:

  • To introduce and demonstrate the utility of commonality analysis (CA) for addressing multicollinearity in spatial genetics.
  • To improve the interpretation of direct gradient analyses by partitioning variance components.
  • To highlight the potential of CA for robust analysis of spatial genetic data.

Main Methods:

  • Utilized simulated datasets and regression analyses on distance matrices.
  • Applied commonality analysis (CA), a variance-partitioning procedure.
  • Decomposed model fit indices into unique and common variance components.

Main Results:

  • CA effectively identifies the presence, location, and magnitude of multicollinearity.
  • The method reveals spurious correlations, enhancing the reliability of multivariate regressions.
  • CA demonstrates potential for managing complex multicollinearity patterns in spatial genetics.

Conclusions:

  • Commonality analysis offers a powerful approach to handle multicollinearity in spatial genetics.
  • Systematic investigation of commonalities is recommended for direct gradient analyses.
  • CA can lead to more accurate conclusions and informed conservation strategies.