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Related Concept Videos

Heritability01:06

Heritability

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" a trait is,...
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
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Updated: May 16, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

SNP-based heritability estimation using a Bayesian approach.

K Krag1, L L Janss, M M Shariati

  • 1Department of Molecular Biology and Genetics, Faculty of Science and Technology, Aarhus University, PO Box 50, DK-8830 Tjele, Denmark. Kristian.Krag@agrsci.dk

Animal : an International Journal of Animal Bioscience
|November 27, 2012
PubMed
Summary
This summary is machine-generated.

Bayesian genomic models accurately estimate heritability using single nucleotide polymorphism (SNP) markers in populations of 400 or more individuals. These methods perform comparably to REML, especially for higher heritability values.

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Area of Science:

  • Quantitative genetics
  • Genomic analysis
  • Statistical modeling

Background:

  • Heritability is crucial in quantitative genetics for understanding genetic contributions to traits.
  • Developing molecular markers like single nucleotide polymorphism (SNP) arrays enhances genetic variance assessment.
  • SNP markers enable heritability estimation even without known family relationships.

Purpose of the Study:

  • To evaluate two Bayesian genomic models for estimating heritability in simulated populations.
  • To compare the performance of Bayesian models against a restricted maximum likelihood (REML) approach.
  • To investigate the impact of family structure and SNP density on heritability estimation accuracy.

Main Methods:

  • Simulated populations with varying family structures and SNP densities were used.
  • Two Bayesian genomic models were employed to estimate heritability.
  • Genotyping and phenotyping were performed on all simulated individuals.

Main Results:

  • Bayesian models accurately estimated heritability (≥0.15) with sample sizes of 400 or more.
  • Models struggled to estimate low heritability (0.05).
  • Bayesian approaches performed similarly to REML, and family structure had minimal impact. Increased SNP density did not significantly improve precision.

Conclusions:

  • Bayesian genomic models are effective for estimating heritability using SNP data in animals with direct measurements.
  • These methods are valuable when quantitative traits are difficult or costly to measure.
  • SNP-based heritability estimation is feasible and reliable under specific conditions.