富集分析框架下的致病SNP位点识别

doi:10.3969/j.issn.1001-2400.2016.03.008

Abstract

Abstract:

Aiming at the recognition of pathogenic SNP loci for complex diseases, this paper proposes an ensemble learning frame via the enrichment analysis mechanism, which can combine different approaches efficiently. Based on the proposed frame, Relief-F and CA trend testing are combined to identify disease-related SNP loci. The new approach can identify not only the single pathogenic site, but also the interaction between the locus at the same time. Experiments have been carried both on simulated data and on real data. Experimental results show that the proposed approach can significantly improve the recognition performance of pathogenic SNP loci for complex diseases. The proposed ensemble learning framework could provide reference for combining different approaches.

Key words: pattern recognition, ensemble learning, interaction, enrichment analysis, recognition of pathogenic single nucleotide polymorphisms loci

YANG Liying;YIN Liyang;YUAN Xiguo;ZHANG Junying. Identifying pathogenic SNP loci by enrichment analysis[J].Journal of Xidian University, 2016, 43(3): 43-48.

References

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Identifying pathogenic SNP loci by enrichment analysis

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