Design, Analysis, and Interpretation of Genome-Wide Association Scans
暫譯: 全基因組關聯掃描的設計、分析與詮釋

Stram, Daniel O.

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商品描述

This book presents the statistical aspects of designing, analyzing and interpreting the results of genome-wide association scans (GWAS studies) for genetic causes of disease using unrelated subjects. Particular detail is given to the practical aspects of employing the bioinformatics and data handling methods necessary to prepare data for statistical analysis. The goal in writing this book is to give statisticians, epidemiologists, and students in these fields the tools to design a powerful genome-wide study based on current technology. The other part of this is showing readers how to conduct analysis of the created study.

Design and Analysis of Genome-Wide Association Studies provides a compendium of well-established statistical methods based upon single SNP associations. It also provides an introduction to more advanced statistical methods and issues. Knowing that technology, for instance large scale SNP arrays, is quickly changing, this text has significant lessons for future use with sequencing data. Emphasis on statistical concepts that apply to the problem of finding disease associations irrespective of the technology ensures its future applications. The author includes current bioinformatics tools while outlining the tools that will be required for use with extensive databases from future large scale sequencing projects. The author includes current bioinformatics tools while outlining additional issues and needs arising from the extensive databases from future large scale sequencing projects.

商品描述(中文翻譯)

本書介紹了設計、分析和解釋基因組廣泛關聯掃描(GWAS 研究)結果的統計方面,重點在於使用無關受試者來探討疾病的遺傳原因。特別詳細地說明了使用生物資訊學和數據處理方法的實際方面,這些方法對於準備數據以進行統計分析是必要的。本書的目標是為統計學家、流行病學家以及這些領域的學生提供設計基於當前技術的強大基因組研究的工具。另一部分則是向讀者展示如何對所創建的研究進行分析。

《基因組廣泛關聯研究的設計與分析》提供了一套基於單一 SNP 關聯的成熟統計方法的彙編。它還介紹了更高級的統計方法和問題。考慮到技術(例如大規模 SNP 陣列)正在迅速變化,本書對未來使用測序數據有重要的啟示。強調適用於尋找疾病關聯問題的統計概念,無論技術如何變化,確保了其未來的應用。作者包括了當前的生物資訊學工具,同時概述了未來大規模測序項目中需要使用的廣泛數據庫所需的工具。作者還包括了當前的生物資訊學工具,並概述了來自未來大規模測序項目所產生的廣泛數據庫所帶來的其他問題和需求。

作者簡介

Dr. Stram's interests center on the application of modern statistical methods to epidemiologic studies: his research includes methods in longitudinal analysis, meta-analysis, survival analysis, and the analysis of errors in exposure measurement and he is well known for his work on the Atomic Bomb survivors study, the Colorado Plateau Uranium Miners study, the Multiethnic Cohort study and on clinical trials of childhood cancer. He has been an investigator and collaborator on many large scale genetic association studies with an emphasis on multi-ethnic analyses, and has published widely on haplotype analysis, analysis of hidden population structure, and the design of multi-stage genotyping and genome-wide association studies.

作者簡介(中文翻譯)

史特拉姆博士的研究興趣集中在現代統計方法在流行病學研究中的應用:他的研究包括縱向分析、統合分析、生存分析以及暴露測量誤差的分析,他因在原子彈倖存者研究、科羅拉多高原鈾礦工研究、多族裔隊列研究以及兒童癌症臨床試驗方面的工作而廣為人知。他在許多大型遺傳關聯研究中擔任研究者和合作者,特別強調多族裔分析,並在單倍型分析、隱藏人口結構分析以及多階段基因分型和全基因組關聯研究的設計方面發表了大量文獻。