SNP specific extraction and analysis using shrunken dissimilarity measure

Yang Liu*, Kwok Po NG, Jin Zhou

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

The identification of genetic variations associated with common disease now plays an important role in human genetics research. In this paper, a new nearest shrunken centroid method was performed to select relevant single nucleotide polymorphisms (SNPs) on a WTCCC Coronary Artery Disease data. This method can succinctly characterize each class (case and control) by shrinking each centroid with respect to the overall centroid by a certain threshold. A relatively high average accuracy of 87% among all 22 chromosomes can be obtained. There are 221 out of 490032 SNPs selected using the proposed shrunken centroid method under a 10-fold cross validation setting. The average number of SNPs being selected is around 10 for each of the chromosome. Comparisons with other shrunken centroid methods were performed, results showed that the performance of the proposed method in terms of accuracy and numbers of selected SNPs is better than others. All computational results show that the proposed shrunken centroid method is a suitable and useful tool to select relevant SNPs with genetic variations in a genome-wide association disease study.

Original languageEnglish
Title of host publication2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
Pages378-381
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 - Niagara Falls, NY, United States
Duration: 2 Aug 20104 Aug 2010

Publication series

Name2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010

Conference

Conference2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
Country/TerritoryUnited States
CityNiagara Falls, NY
Period2/08/104/08/10

Scopus Subject Areas

  • Biomedical Engineering
  • Health Information Management

User-Defined Keywords

  • Categorical
  • Classification
  • Mode
  • Shrunken centroid
  • SNP

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