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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.
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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...
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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).
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The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
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Testing Hardy-Weinberg disequilibrium using the generalized linear model.

Shizhong Xu1

  • 1Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA. shizhong.xu@ucr.edu

Genetics Research
|December 20, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for jointly detecting Hardy-Weinberg disequilibrium (HWD) across multiple genetic loci, improving accuracy and reducing false positives from linkage disequilibrium (LD). An R package,

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Area of Science:

  • Population Genetics
  • Statistical Genetics

Background:

  • Traditional Hardy-Weinberg disequilibrium (HWD) detection methods analyze loci individually.
  • Existing methods can be susceptible to false positives, particularly when linkage disequilibrium (LD) is present.

Purpose of the Study:

  • To develop a novel statistical method for the joint detection of HWD across multiple genetic loci.
  • To improve the power and accuracy of HWD detection compared to single-locus methods.
  • To mitigate false positives arising from LD in population genetic analyses.

Main Methods:

  • Developed a generalized linear model (GLM) with a probit link function for joint HWD detection.
  • The method was evaluated for its performance on single loci and across multiple loci.
  • An R package, 'hwdglm', was created for practical implementation of the joint HWD detection method.

Main Results:

  • The proposed method demonstrates higher statistical power than the exact test for single-locus HWD detection.
  • Joint analysis of multiple loci effectively reduces false positive HWD detections caused by LD.
  • Application to 24 SNP markers in a human gene successfully identified and corrected false positive HWDs.

Conclusions:

  • The novel GLM-based approach provides a more powerful and accurate method for detecting HWD.
  • Joint HWD detection is crucial for accurate population genetic inferences, especially in the presence of LD.
  • The 'hwdglm' R package offers a valuable tool for researchers to implement this advanced HWD detection technique.