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Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
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Haplotype Inference.

Sunah Song1, Xin Li1, Jing Li2

  • 1Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH, 44106, USA.

Methods in Molecular Biology (Clifton, N.J.)
|October 6, 2017
PubMed
Summary
This summary is machine-generated.

Haplotypes reveal crucial genetic patterns for disease research but are not directly measured. This chapter presents four methods to reconstruct these important haplotype sequences from genotype data for both unrelated individuals and families.

Keywords:
FASTPHASEGenotypeHaplotypeLinkage disequilibriumMACHMendelian lawMerlinPedPhase 3.0PedigreePopulation

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Haplotypes, representing linked nucleotide variants, are vital for understanding human disease genetics.
  • High-throughput genotyping platforms do not directly provide haplotype information.
  • Reconstructing haplotypes from genotype data is essential for genetic analysis.

Purpose of the Study:

  • To introduce methods for reconstructing haplotypes from unphased genotype data.
  • To cover techniques applicable to both unrelated individuals and family-based studies.
  • To provide a comprehensive overview of haplotype reconstruction approaches.

Main Methods:

  • The chapter details four representative computational methods for haplotype reconstruction.
  • Two methods are specifically designed for unrelated individuals.
  • Two methods are tailored for family-based genetic data.

Main Results:

  • The presented methods enable the inference of haplotype information from readily available genotype data.
  • These approaches facilitate a deeper understanding of genetic linkage patterns.
  • The chapter provides a comparative overview of different reconstruction strategies.

Conclusions:

  • Haplotype reconstruction is a key step in leveraging genotype data for disease genetics research.
  • The discussed methods offer valuable tools for geneticists and bioinformaticians.
  • Accurate haplotype inference aids in identifying disease-associated genetic variations.