2013 QuadraticOptimizationtoIdentify

• (Sun et al., 2013) ⇒ Jiangwen Sun, Jinbo Bi, and Henry R. Kranzler. (2013). “Quadratic Optimization to Identify Highly Heritable Quantitative Traits from Complex Phenotypic Features.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-2174-7 doi:10.1145/2487575.2487621

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Cited By

• http://scholar.google.com/scholar?q=%222013%22+Quadratic+Optimization+to+Identify+Highly+Heritable+Quantitative+Traits+from+Complex+Phenotypic+Features
• http://dl.acm.org/citation.cfm?id=2487575.2487621&preflayout=flat#citedby

Quotes

Author Keywords

• Data mining; heritability; quadratic optimization; quadratic programming methods; quantitative trait

Abstract

Identifying genetic variation underlying a complex disease is important. Many complex diseases have heterogeneous phenotypes and are products of a variety of genetic and environmental factors acting in concert. Deriving highly heritable quantitative traits of a complex disease can improve the identification of genetic risk of the disease. The most sophisticated methods so far perform unsupervised cluster analysis on phenotypic features; and then a quantitative trait is derived based on each resultant cluster. Heritability is estimated to assess the validity of the derived quantitative traits. However, none of these methods explicitly maximize the heritability of the derived traits. We propose a quadratic optimization approach that directly utilizes heritability as an objective during the derivation of quantitative traits of a disease. This method maximizes an objective function that is formulated by decomposing the traditional maximum likelihood method for estimating heritability of a quantitative trait. We demonstrate the effectiveness of the proposed method on both synthetic data and real-world problems. We apply our algorithm to identify highly heritable traits of complex human-behavior disorders including opioid and cocaine use disorders, and highly heritable traits of dairy cattle that are economically important. Our approach outperforms standard cluster analysis and several previous methods.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 QuadraticOptimizationtoIdentify	Jiangwen Sun Jinbo Bi Henry R. Kranzler			Quadratic Optimization to Identify Highly Heritable Quantitative Traits from Complex Phenotypic Features				10.1145/2487575.2487621		2013