SKM-SNP: SNP markers detection method

Yang Liu, Mark Li, Yiu Ming CHEUNG, Pak C. Sham, Kwok Po NG*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

SKM-SNP, SNP markers detection program, is proposed to identify a set of relevant SNPs for the association between a disease and multiple marker genotypes. We employ a subspace categorical clustering algorithm to compute a weight for each SNP in the group of patient samples and the group of normal samples, and use the weights to identify the subsets of relevant SNPs that categorize these two groups. The experiments on both Schizophrenia and Parkinson Disease data sets containing genome-wide SNPs are reported to demonstrate the program. Results indicate that our method can find some relevant SNPs that categorize the disease samples. The online SKM-SNP program is available at http://www.math.hkbu.edu.hk/~mng/SKM-SNP/SKM-SNP.html.

Original languageEnglish
Pages (from-to)233-239
Number of pages7
JournalJournal of Biomedical Informatics
Volume43
Issue number2
DOIs
Publication statusPublished - Apr 2010

Scopus Subject Areas

  • Computer Science Applications
  • Health Informatics

User-Defined Keywords

  • K-mode
  • Single nucleotide polymorphism
  • SKM-SNP
  • Subspace clustering

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