• DocumentCode
    3409972
  • Title

    High-throughput microarray-based genotyping

  • Author

    Yang, Geoffrey ; Ho, Ming-Hsiu ; Hubbell, Earl

  • fYear
    2004
  • fDate
    16-19 Aug. 2004
  • Firstpage
    586
  • Lastpage
    587
  • Abstract
    A high throughput genotyping platform that scores over 10,000 single-nucleotide polymorphisms (SNPs) per individual on a single GeneChip® high-density oligonucleotide microarray has been developed to conduct studies to elucidate the genetic basis for complex diseases. Currently, the genotyping of individual SNPs relies on the summary statistics (based on the observed intensities of probes on the microarray) for the entirety of the sample set. A classification scheme of those statistics across hundreds of individual DNA samples is obtained to make individual genotyping calls. In contrast to the current approach, the method in this work makes individual genotyping call by finding the minimum residual, i.e. highest likelihood, among four possible states corresponding to three genotypes and no-call. Initially, the residual is calculated based on a given set of probe affinities for that individual sample. Auspiciously, the multitude of samples was utilized to iterate to refine the probe affinities, sample concentration, and background intensities. These refined parameters entail an improved call rate while maintaining high accuracy.
  • Keywords
    DNA; classification; diseases; genetics; medical computing; molecular biophysics; polymorphism; statistics; GeneChip high-density oligonucleotide microarray; background intensities; classification scheme; complex diseases; genotyping-calling approach; high-throughput microarray-based genotyping; individual DNA samples; probe affinities; sample concentration; single-nucleotide polymorphisms; summary statistics; Bioinformatics; Clustering algorithms; DNA; Diseases; Frequency; Genetics; Probes; Robustness; Statistics; Throughput;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Systems Bioinformatics Conference, 2004. CSB 2004. Proceedings. 2004 IEEE
  • Print_ISBN
    0-7695-2194-0
  • Type

    conf

  • DOI
    10.1109/CSB.2004.1332507
  • Filename
    1332507