Reliable identification of large numbers of candidate SNPs from public EST data

Kenneth H. Buetow, Michael N. Edmonson, Anna B. Cassidy

Research output: Contribution to journalArticlepeer-review

223 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)323-325
Number of pages3
JournalNature Genetics
Issue number3
StatePublished - Mar 1 1999
Externally publishedYes

ASJC Scopus subject areas

  • Genetics


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