Chinese Journal of Tissue Engineering Research ›› 2011, Vol. 15 ›› Issue (17): 3191-3195.doi: 10.3969/j.issn.1673-8225.2011.17.036

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Single nucleotide polymorphism and application of epistatic dominance communication in rheumatoid disease explored by random forest sliding window

Yan Lu-ying1, Hua Lin1, Yan Yan1   

  1. 1Microport Medical (Shanghai) Co., Ltd., Shanghai  201203, China
    2Institute of Biomedical Engineering, Capital Medical University, Beijing  100069, China
  • Received:2010-11-04 Revised:2011-01-20 Online:2011-04-23 Published:2011-04-23
  • Contact: Yan Yan, Master, Associate professor, Institute of Biomedical Engineering, Capital Medical University, Beijing 100069, China yy2703@163.com
  • About author:Yan Lu-ying, Intermediate engineer, Microport Medical (Shanghai) Co., Ltd., Shanghai 201203, China lyyan@microport.com
  • Supported by:

    Capital Medical University Basis-Clinical Research Cooperation Fund, No.09JL35*

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Abstract:

BACKGROUND: Rheumatoid Arhtritis (RA) is a complex polygene genetic disease. The traditional genetics is difficult to analyze high throughput rheumatoid disease (RD) data, and to identify the genetic markers associated with disease.
OBJECTIVE: To abstract the new target genes associated with RA by data mining method.
METHODS: Single nucleotide polymorphism (SNP) of RD was explored by random forest sliding window. First, gini importance of each SNP was sorting from the largest to the smallest. In the following step, a sliding window sequential forward algorithm that added one SNP at a time was applied to construct a subset of SNPs, which was used to compute the classification error rate of out of bag (OOB) as categorical variables set. We filtered a set of feature SNPs, which could minimize the classification error. Furthermore, we applied polymorphism interaction analysis (PIA) algorithm to explore two-way and three-way interactions among feature SNPs.
RESULTS AND CONCLUSION: The results showed that many of feature SNPs associated with RA are validated by previous reports. In addition, the interaction analysis results might provide some theoretical basis for the research of disease.

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