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Methods in Genetics and Clinical Interpretation

Analysis of Complex Disease Association and Linkage Studies Using the University of California Santa Cruz Genome Browser

Tianyuan Wang, MS and Terrence S. Furey, PhD

From the Center for Human Genetics (T.W.), Duke University Medical Center; and Institute for Genome Sciences & Policy (T.S.F.), Duke University, Durham, NC.

Correspondence to Terrence S. Furey, PhD, Institute for Genome Sciences & Policy, Duke University, 101 Science Drive, Box 3382, Durham, NC 27708. E-mail terry.furey@duke.edu

Key Words: cardiovascular diseases • computers • mapping • genomics • GWAS

An extract of the first 250 words of the full text is provided, because this article has no abstract.

	Introduction

 
The sequencing of the human genome, the identification of common single-nucleotide polymorphisms (SNPs) and haplotype blocks, and advances in microarray technology have enabled the study of complex diseases at a level of detail not previously imaginable. These have aided in the design and analyses of association and linkage studies of many complex diseases including cardiovascular disease. Recent technological advances have enabled the undertaking of large-scale genome-wide association studies (GWAS) that can assay hundreds of thousands of polymorphic sites on hundreds to thousands of individuals to find genomic regions associated with disease. Although results from these experiments enable the identification of smaller regions of association compared with previous studies, as with all linkage and association studies, there is the need for the further investigation of regions of interest for the causal genes or variants.

The purpose of this review is to present a detailed demonstration as to how publicly available resources can be used to easily guide more detailed research into genomic regions of interest identified in linkage and association study data. Large-scale projects, such as the Human Genome Sequencing project,^1,2 have generated large volumes and varieties of annotated genomic data necessitating the development of Internet-based tools to organize and make practically available these public data. One important tool in human disease research is the web-based graphical genome browsers that use the human genome sequence as the framework on which to organize genomic annotations, providing various ways for researchers to view and extract important information. Currently, there are 3 human genome . . . [Full Text of this Article]