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Related Concept Videos

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...
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
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Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

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.
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance, comparing...
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.
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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,...

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Related Experiment Video

Updated: May 18, 2026

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

Parameter estimation and quantitative parametric linkage analysis with GENEHUNTER-QMOD.

Thomas Künzel1, Konstantin Strauch

  • 1Institute of Medical Biometry and Epidemiology, Philipps University Marburg, Marburg, Germany. thomas.kuenzel@accovion.com

Human Heredity
|September 6, 2012
PubMed
Summary
This summary is machine-generated.

We developed GENEHUNTER-QMOD, a new parametric method for quantitative trait linkage analysis. This tool offers improved power for complex pedigrees and non-normal data, providing a valuable resource for genetic research.

Related Experiment Videos

Last Updated: May 18, 2026

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

Area of Science:

  • Genetics
  • Biostatistics

Background:

  • Quantitative phenotypes are crucial for understanding complex diseases.
  • Accurate linkage analysis is essential for identifying disease-related genes.

Purpose of the Study:

  • To introduce a novel parametric method for linkage analysis of quantitative phenotypes.
  • To provide a tool for estimating phenotype parameters alongside linkage testing.
  • To evaluate the performance of the new method through simulations.

Main Methods:

  • Phenotype modeling using normally distributed variables with genotype-specific distributions.
  • Parameter estimation via maximizing the LOD score using the PGRAD gradient-based optimization method.
  • Implementation in the GENEHUNTER-QMOD software.

Main Results:

  • The PGRAD method shows lower power than variance components analysis (VCA) for normal distributions and small pedigrees.
  • PGRAD outperforms VCA and Haseman-Elston regression for extended pedigrees, nonrandomly ascertained data, and non-normally distributed phenotypes.
  • While PGRAD demonstrates higher power and conservativeness, VCA shows an inflated type I error rate; parameter estimation may underestimate residual variances but performs better for expectation values.

Conclusions:

  • GENEHUNTER-QMOD offers a powerful new tool for explicitly modeling quantitative phenotypes in linkage analysis.
  • The software is freely available for researchers.
  • This method enhances the ability to model complex genetic traits.