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Related Experiment Videos

How many SNPs does a genome-wide haplotype map require?

Richard Judson1, Benjamin Salisbury, Julie Schneider

  • 1Genaissance Pharmaceuticals, 5 Science Park, New Haven, CT 06511, USA. r.judson@genaissance.com

Pharmacogenomics
|June 8, 2002
PubMed
Summary
This summary is machine-generated.

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Estimating the number of single nucleotide polymorphisms (SNPs) for a complete human genome haplotype survey ranges from 180,000 to 600,000. The required number depends on sample size and ethnic diversity, impacting cost and effort.

Area of Science:

  • Genomics
  • Human Genetics
  • Bioinformatics

Background:

  • Haplotype surveys are crucial for understanding human genetic variation.
  • Previous studies have provided initial estimates for SNP requirements.
  • The composition of reference populations significantly influences these estimates.

Purpose of the Study:

  • To derive and compare estimates for the number of single nucleotide polymorphisms (SNPs) needed for a comprehensive human genome haplotype survey.
  • To analyze the impact of sample size and ethnic diversity on SNP requirements.
  • To assess the feasibility and cost of conducting such a survey.

Main Methods:

  • Utilizing data and reports from published studies (Stephens et al., Patil et al., Daly et al.).
  • Developing computational models to estimate SNP numbers based on different population parameters.

Related Experiment Videos

  • Analyzing the relationship between sample characteristics and required SNP density.

    • Main Results:

    • Estimated SNP numbers for a genome-wide haplotype survey range from 180,000 (European sample, 16 chromosomes) to 600,000 (diverse sample, 164 chromosomes).
    • The size and ethnic composition of the study cohort are critical factors influencing the required SNP count.
    • Public SNP databases can contribute to the efficiency of this effort.

    Conclusions:

    • A varying number of SNPs are necessary for a complete human genome haplotype survey, contingent upon population specifics.
    • Strategic selection of sample cohorts and leveraging public resources are key to optimizing the survey.
    • The findings provide a basis for planning future large-scale genomic studies and estimating associated costs.