This preview shows pages 1–2. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.View Full Document
Unformatted text preview: BIOINFORMATICS ORIGINAL PAPER Vol. 25 no. 2 2009, pages 237242 doi:10.1093/bioinformatics/btn613 Genetics and population analysis Prioritizing risk pathways: a novel association approach to searching for disease pathways fusing SNPs and pathways Lina Chen , , Liangcai Zhang , Yan Zhao , Liangde Xu , Yukui Shang, Qian Wang, Wan Li, Hong Wang and Xia Li , College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China Received on August 1, 2008; revised on October 27, 2008; accepted on November 21, 2008 Advance Access publication November 24, 2008 Associate Editor: Alex Bateman ABSTRACT Motivation: Complex diseases are generally thought to be under the inuence of one or more mutated risk genes as well as genetic and environmental factors. Many traditional methods have been developed to identify susceptibility genes assuming a single-gene disease model (single-locus methods). Pathway-based approaches, combined with traditional methods, consider the joint effects of genetic factor and biologic network context. With the accumulation of high-throughput SNP datasets and human biologic pathways, it becomes feasible to search for risk pathways associated with complex diseases using bioinformatics methods. By analyzing the contribution of genetic factor and biologic network context in KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, we proposed an approach to prioritize risk pathways for complex diseases: Prioritizing Risk Pathways fusing SNPs and pathways (PRP). A risk-scoring (RS) measurement was used to prioritize risk biologic pathways. This could help to demonstrate the pathogenesis of complex diseases from a new perspective and provide new hypotheses. We introduced this approach to five complex diseases and found that these five diseases not only share common risk pathways, but also have their specific risk pathways, which is verified by literature retrieval. Availability: Genotype frequencies of five casecontrol samples were downloaded from the WTCCC online system and the address is https://www.wtccc.org.uk/info/access_to_data_samples.shtml Contact: email@example.com; firstname.lastname@example.org Supplementary information: Supplementary data are available at Bioinformatics online. 1 INTRODUCTION Complex diseases are known to arise from one or more mutated genes as well as genetic and environmental factors. One major challenge of the post-genomic era is to find the genes at risk, identify their functions and develop new techniques for testing, diagnosis and treatment (Mocellin et al ., 2004). The complexity of these diseases cannot be interpreted by a single gene product or the behavior of a single specific pathway. Their pathogenesis should be interpreted with the effects of genetic and environmental factors together To whom correspondence should be addressed....
View Full Document
This note was uploaded on 04/06/2010 for the course COMPUTER S COSC1520 taught by Professor Paul during the Spring '09 term at York University.
- Spring '09
- Machine Learning