Applied and Translational Genomics for Human Genetics and Clinical Science

A book review based on Applied Computational Genomics (Translational Bioinformatics Volume 1) Edited by Yin Yao Shugart Springer; 2012; ISBN: 978-94-007-5557-4; Hardcover; 184 pp.; $189.00. Translational bioinformatics is an emerging field of study that addresses the computational challenges encountered in biological and clinical research as well as in the analysis and interpretation of the data generated from it. Applied computation genomics, as part of the Springer Series on Translational Bioinformatics, thoroughly discusses the most relevant issues in the development of novel techniques for the integration of human genetic, biological, and clinical data. This book also provides an example of theories and research being practically applied to inform translational medical research in clinical diagnosis. This book covers numerous experimental and computational methods related to statistical development and their applications in the field of human genomics, including candidate gene mapping, linkage analysis, population-based, genome-wide association, exon sequencing, and whole genome sequencing analysis. This book consists of ten chapters. The first chapter focuses on an overview of the current human genome science. It reviews the history of using machine-learning algorithms for studies on disease prediction and provides highlights for the other nine chapters, which have been collected in this book. Chapter 2 provides a broad overview of the most important concepts in genetic epidemiology. In this chapter, the authors provide a precise definition for complex traits and a thorough introduction to genetic epidemiology as a tool for understanding the role of genetic factors. In addition, the essential study designs used to accomplish this goal, including family, twin, adoption, and migration studies, are summarized. Chapter 3 focuses on integrated linkage analysis and its results in the design, execution, and interpretation of whole genome or whole exome sequencing studies. It includes experiments, knowledge, and specific example data. This chapter also presents new statistical algorithms to identify rare variants in pedigree settings for both qualitative and quantitative traits. Chapter 4 briefly reviews the methods used to combine functional genomic data to detect complex diseases. Chapter 4 examines the progress of research on a specific rare disorder, nasopharyngeal carcinoma (NPC). Dr. Jorgensen et al. conducted a thorough review of all candidate genes related to NPC and explained the findings of two genome-wide association studies (GWAS), one by a