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Related Concept Videos

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.In the early 20th century,...
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...
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Test for Homogeneity

The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can be stated as...
Types of Hypothesis Testing01:11

Types of Hypothesis Testing

There are three types of hypothesis tests: right-tailed, left-tailed, and two-tailed.
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Statistical Hypothesis Testing01:16

Statistical Hypothesis Testing

Hypothesis testing is a critical statistical procedure facilitating informed, evidence-based decisions. It begins with a hypothesis, which is a tentative explanation, or a prediction about a population parameter. This hypothesis can be either a null hypothesis (H0), indicating no effect or difference, or an alternative hypothesis (Ha), suggesting an effect or difference.
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Related Experiment Video

Updated: Jun 25, 2026

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

Robust testing of haplotype/disease association.

Andrew S Allen1, Glen A Satten

  • 1Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA. andrew.s.allen@duke.edu

BMC Genetics
|February 3, 2006
PubMed
Summary

This study evaluates a new statistical method for analyzing genetic data to understand complex diseases. The approach helps resolve genetic ambiguities, improving the study of haplotype-disease associations.

Area of Science:

  • Genetics
  • Statistical genetics
  • Computational biology

Background:

  • Haplotypes, combinations of linked alleles on a chromosome, are crucial for studying complex diseases.
  • Statistical methods are needed to resolve haplotype phase ambiguity when only genotype data are available.

Purpose of the Study:

  • To evaluate a novel statistical approach for testing and estimating haplotype-disease associations.
  • To assess the performance of this approach using simulated genetic data.

Main Methods:

  • Application of a recently developed statistical method for haplotype-disease association analysis.
  • Utilizing simulated multilocus genotype data from the Genetic Analysis Workshop 14.

Main Results:

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  • The proposed statistical approach was applied to simulated data.
  • Evaluation of the method's performance in resolving haplotype phase ambiguity and testing associations.
  • Conclusions:

    • The evaluated statistical approach shows promise for analyzing genetic components of complex diseases.
    • The method's invariance to population genetic structure is a key advantage for association studies.