Reliable Identification of Large Numbers of Candidate SNPs From Public EST Data

Nat Genet. 1999 Mar;21(3):323-5. doi: 10.1038/6851.

Abstract

High-resolution genetic analysis of the human genome promises to provide insight into common disease susceptibility. To perform such analysis will require a collection of high-throughput, high-density analysis reagents. We have developed a polymorphism detection system that uses public-domain sequence data. This detection system is called the single nucleotide polymorphism pipeline (SNPpipeline). The analytic core of the SNPpipeline is composed of three components: PHRED, PHRAP and DEMIGLACE. PHRED and PHRAP are components of a sequence analysis suite developed to perform the semi-automated analysis required for large-scale genomes (provided courtesy of P. Green). Using these informatics tools, which examine redundant raw expressed sequence tag (EST) data, we have identified more than 3,000 candidate single-nucleotide polymorphisms (SNPs). Empiric validation studies of a set of 192 candidates indicate that 82% identify variation in a sample of ten Centre d'Etudes Polymorphism Humain (CEPH) individuals. Our results suggest that existing sequence resources may serve as a valuable source for identifying genetic variation.

MeSH terms

  • Algorithms
  • Databases, Factual*
  • Expressed Sequence Tags*
  • Gene Frequency
  • Genetic Variation
  • Genetics, Population
  • Heterozygote
  • Humans
  • Internet
  • Nucleotides / genetics
  • Polymerase Chain Reaction
  • Polymorphism, Restriction Fragment Length*
  • Reproducibility of Results
  • Software

Substances

  • Nucleotides