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

Mutation, Gene Flow, and Genetic Drift

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).

Biostatistics: Overview

Biostatistics: Overview

Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...

Statistical Analysis: Overview

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...

Statistical Methods for Analyzing Epidemiological Data

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:

Genetic Variation

Genetic Variation

Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles,...

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

You might also read

Related Articles

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

Sort by

Same author

Methods to estimate marine functional connectivity: A primer.

Ecological applications : a publication of the Ecological Society of America·2026

Same author

The diffusion of cooperative and solo bubble net feeding in Canadian Pacific humpback whales.

Proceedings. Biological sciences·2026

Same author

Phylogeographic and Ecological Insights Into the Evolutionary History of the Grass- and Sedge-Specializing Deltocephalinae Leafhoppers.

Ecology and evolution·2026

Same author

Post-pleistocene colonisation rather than the contemporary environment has most influenced the current population structure of Scottish Atlantic salmon (Salmo salar).

PloS one·2025

Same author

A method for identifying local adaptation in structured populations.

PLoS genetics·2025

Same author

Chromosome-level genome assembly of Pinus massoniana provides insights into conifer adaptive evolution.

GigaScience·2025

Same journal

From Gene Copies to Cell Numbers: Advancing Quantitative Approaches in Protistan Ecology Using Digital PCR.

Molecular ecology resources·2026

Same journal

EasyCen: A Lightweight Framework for Centromere Localisation and Repeat-Organisation Profiling in Telomere-to-Telomere Genomes.

Molecular ecology resources·2026

Same journal

A Practical Framework for GT-Seq Panel Optimization.

Molecular ecology resources·2026

Same journal

Comparison of Environmental DNA and Bulk DNA Metabarcoding for Assessing Terrestrial Arthropod Diversity Across Three Habitat Types on Guam.

Molecular ecology resources·2026

Same journal

pr2-Wormifier: A Bioinformatics Pipeline to Create Custom Reference Databases for Improved Metabarcoding of Marine Protists.

Molecular ecology resources·2026

Same journal

Individual Identification of Prey in Carnivore Scats.

Molecular ecology resources·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Oct 1, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Information-based summary statistics for spatial genetic structure inference.

Xinghu Qin¹, Oscar E Gaggiotti¹

¹Centre for Biological Diversity, University of St Andrews, Fife, UK.

Molecular Ecology Resources

|March 7, 2022

Summary

This summary is machine-generated.

Information-based statistics, like Shannon differentiation (ΔD), and Jaccard dissimilarity (J) show strong potential for measuring spatial genetic diversity. These novel approaches may outperform traditional methods in population genetics.

Keywords:

information-based statistics population genetics spatial structure

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

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Related Experiment Videos

Last Updated: Oct 1, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

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

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Area of Science:

Ecology and Evolutionary Biology
Population Genetics
Biodiversity Measurement

Background:

Biodiversity measurement is crucial for understanding ecological and evolutionary processes driving spatial patterns.
Ecologists utilize information-based summary statistics, such as Hill numbers, for biodiversity assessment.
Population genetics traditionally relies on heterozygosity and allelic richness, but information-based statistics are emerging.

Purpose of the Study:

To comprehensively assess the effectiveness of information-based summary statistics in revealing spatial genetic diversity patterns.
To compare the performance of information-based statistics against traditional population genetics measures (allelic richness, heterozygosity).

Main Methods:

Defined three sets of summary statistics: allelic richness (Jaccard index), heterozygosity (F_ST), and Hill numbers (Shannon entropy, ΔD).
Employed three machine learning methods for unbiased evaluation of the discriminatory power of these statistic sets.
Tested the ability of each set to distinguish between different spatial scenarios.

Main Results:

Information-based measures, particularly Shannon differentiation (ΔD), performed comparably or better than traditional methods in some spatial scenarios.
Jaccard dissimilarity (J), a measure based on allelic richness, exhibited the highest discriminatory power among spatial scenarios.
Shannon differentiation (ΔD) also demonstrated strong performance, ranking second in discriminatory power.

Conclusions:

Information-based measures and Jaccard dissimilarity are valuable additions to the population genetics toolkit for analyzing spatial genetic diversity.
These novel approaches offer enhanced power to discern spatial patterns compared to traditional metrics.