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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,...
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Determination of the Mating Efficiency of Haploids in Saccharomyces cerevisiae
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Entropy-supported marker selection and Mantel statistics for haplotype sharing analysis.

Anke Schulz1, Christine Fischer, Jenny Chang-Claude

  • 1Division of Cancer Epidemiology, Unit of Genetic Epidemiology, German Cancer Research Center DKFZ, Im Neuenheimer Feld 280, Heidelberg, Germany.

Genetic Epidemiology
|February 13, 2010
PubMed
Summary

This study introduces a novel algorithm combining entropy-based marker selection with haplotype sharing Mantel statistics for complex disease research. This approach improves the detection of disease-associated genetic markers by optimizing marker selection for haplotype analysis.

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Area of Science:

  • Genetics
  • Statistical Genetics
  • Computational Biology

Background:

  • Haplotype sharing analysis is crucial for investigating complex disease etiology.
  • The statistical power of haplotype association methods relies on capturing information from unobserved haplotypes using multilocus genotypes.

Purpose of the Study:

  • To develop and evaluate a new algorithm that integrates an entropy-based marker selection (EMS) algorithm with haplotype sharing-based Mantel statistics.
  • To enhance the detection of disease-associated single nucleotide polymorphisms (SNPs) and flanking markers in genetic association studies.

Main Methods:

  • A novel algorithm combining EMS with haplotype sharing-based Mantel statistics was developed.
  • Genetic markers were iteratively selected based on multilocus linkage disequilibrium (LD), assessed via normalized entropy difference.
  • Markers were added to increase information on sharing around potential susceptibility markers and removed if they did not improve multilocus LD.

Main Results:

  • The combined EMS and Mantel statistics approach performed as well as or better than standard Mantel statistics and sliding window methods in simulated candidate gene studies.
  • The algorithm demonstrated effectiveness in detecting disease SNPs and their flanking markers through indirect association analysis.

Conclusions:

  • The proposed marker selection approach is effective for haplotype-based association analysis.
  • This data-driven selection method avoids arbitrary marker choices associated with fixed window sizes and complex haplotype block structure estimation.