• DocumentCode
    472222
  • Title

    Cancer Classification Using Loss of Heterozygosity Data Derived from Single-Nucleotide Polymorphism Genotyping Arrays

  • Author

    Wang, Yuhang

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Southern Methodist Univ., Dallas, TX
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    5864
  • Lastpage
    5867
  • Abstract
    Single-Nucleotide Polymorphism (SNP) array is a recently introduced technology that genotypes more than 10,000 human SNPs on a single array. It has been shown that genome-wide Loss of Heterozygosity (LOH) calls can be derived by analyzing the genotypes calls measured by SNP arrays using paired tumor and normal tissue samples. The goal of this study is to evaluate the possibility of cancer classification using LOH calls. As a proof of concept, we applied 16 different combinations of classification algorithms and feature selection algorithms to a public data set that contains LOH calls of 10,043 SNP loci obtained from 10 breast cancer patients and 5 small cell lung cancer (SCLC) patients. Performance was measured in terms of the leave-one-out cross-validation (LOOCV) classification accuracy. Experimental results suggest that LOH calls derived from SNP arrays can be an excellent indicator of cancer type
  • Keywords
    cancer; cellular biophysics; genetics; gynaecology; learning (artificial intelligence); medical computing; molecular biophysics; pattern classification; polymorphism; support vector machines; tumours; breast cancer classification; feature selection algorithm; genome; genotype analysis; human single-nucleotide polymorphism genotyping arrays; leave-one-out cross-validation classification accuracy; loss-of-heterozygosity data; machine learning; normal tissue samples; paired tumor; public data set; small cell lung cancer patient; support vector machine; Bioinformatics; Cancer; Classification algorithms; Gene expression; Genomics; Humans; Loss measurement; Machine learning; Machine learning algorithms; Neoplasms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.260116
  • Filename
    4463141