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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.
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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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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Robust and Powerful Affected Sibpair Test for Rare Variant Association.

Keng-Han Lin1,2, Sebastian Zöllner1,2,3

  • 1Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America.

Genetic Epidemiology
|May 14, 2015
PubMed
Summary

We introduce TRAFIC, a novel family-based method for rare variant association testing in affected sibpairs. TRAFIC offers superior power and robustness to population stratification compared to traditional case-control studies for complex diseases.

Keywords:
association testdichotomous traitsfamily studiesrare variantssequencing

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Area of Science:

  • Genetics
  • Genomic Medicine
  • Statistical Genetics

Background:

  • Advances in DNA sequencing enable rare variant analysis in complex diseases.
  • Conventional case-control studies require large samples and are susceptible to population stratification.
  • Family-based designs offer advantages for rare variant association testing, especially with affected relatives.

Purpose of the Study:

  • To propose a novel framework for rare variant association testing in affected sibpairs.
  • To enhance power and mitigate population stratification in genetic association studies.
  • To introduce a family-based internal control method for rare variant analysis.

Main Methods:

  • Developed the Test for Rare Variant Association with Family-based Internal Control (TRAFIC) framework.
  • Compared allele counts of rare variants in shared vs. nonshared chromosomal regions within sibpairs.
  • Evaluated statistical power analytically for various genetic models and allele frequencies.

Main Results:

  • TRAFIC demonstrates superior power over case-control studies for rare variants (risk allele frequency < 0.05).
  • The method is robust to population stratification due to within-family matching.
  • Power advantage is amplified with allelic heterogeneity and depends on interaction complexity and heritability.

Conclusions:

  • TRAFIC provides a powerful and robust approach for rare variant association testing in affected sibpairs.
  • This method addresses limitations of conventional designs in complex disease genetics.
  • Freely available software is provided to facilitate the application of TRAFIC.