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Pathway-based identification of SNPs predictive of survival.

Publication ,  Journal Article
Pang, H; Hauser, M; Minvielle, S
Published in: Eur J Hum Genet
June 2011

In recent years, several association analysis methods for case-control studies have been developed. However, as we turn towards the identification of single nucleotide polymorphisms (SNPs) for prognosis, there is a need to develop methods for the identification of SNPs in high dimensional data with survival outcomes. Traditional methods for the identification of SNPs have some drawbacks. First, the majority of the approaches for case-control studies are based on single SNPs. Second, SNPs that are identified without incorporating biological knowledge are more difficult to interpret. Random forests has been found to perform well in gene expression analysis with survival outcomes. In this paper we present the first pathway-based method to correlate SNP with survival outcomes using a machine learning algorithm. We illustrate the application of pathway-based analysis of SNPs predictive of survival with a data set of 192 multiple myeloma patients genotyped for 500,000 SNPs. We also present simulation studies that show that the random forests technique with log-rank score split criterion outperforms several other machine learning algorithms. Thus, pathway-based survival analysis using machine learning tools represents a promising approach for the identification of biologically meaningful SNPs associated with disease.

Duke Scholars

Published In

Eur J Hum Genet

DOI

EISSN

1476-5438

Publication Date

June 2011

Volume

19

Issue

6

Start / End Page

704 / 709

Location

England

Related Subject Headings

  • Survival Analysis
  • Predictive Value of Tests
  • Polymorphism, Single Nucleotide
  • Multiple Myeloma
  • Models, Genetic
  • Metabolic Networks and Pathways
  • Humans
  • Genotype
  • Genetics & Heredity
  • Genetic Predisposition to Disease
 

Citation

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Pang, H., Hauser, M., & Minvielle, S. (2011). Pathway-based identification of SNPs predictive of survival. Eur J Hum Genet, 19(6), 704–709. https://doi.org/10.1038/ejhg.2011.3
Pang, Herbert, Michael Hauser, and Stéphane Minvielle. “Pathway-based identification of SNPs predictive of survival.Eur J Hum Genet 19, no. 6 (June 2011): 704–9. https://doi.org/10.1038/ejhg.2011.3.
Pang H, Hauser M, Minvielle S. Pathway-based identification of SNPs predictive of survival. Eur J Hum Genet. 2011 Jun;19(6):704–9.
Pang, Herbert, et al. “Pathway-based identification of SNPs predictive of survival.Eur J Hum Genet, vol. 19, no. 6, June 2011, pp. 704–09. Pubmed, doi:10.1038/ejhg.2011.3.
Pang H, Hauser M, Minvielle S. Pathway-based identification of SNPs predictive of survival. Eur J Hum Genet. 2011 Jun;19(6):704–709.

Published In

Eur J Hum Genet

DOI

EISSN

1476-5438

Publication Date

June 2011

Volume

19

Issue

6

Start / End Page

704 / 709

Location

England

Related Subject Headings

  • Survival Analysis
  • Predictive Value of Tests
  • Polymorphism, Single Nucleotide
  • Multiple Myeloma
  • Models, Genetic
  • Metabolic Networks and Pathways
  • Humans
  • Genotype
  • Genetics & Heredity
  • Genetic Predisposition to Disease