<電子ブック>
Design, Analysis, and Interpretation of Genome-Wide Association Scans / by Daniel O. Stram
(Statistics for Biology and Health. ISSN:21975671)
版 | 1st ed. 2014. |
---|---|
出版者 | (New York, NY : Springer New York : Imprint: Springer) |
出版年 | 2014 |
本文言語 | 英語 |
大きさ | XV, 334 p. 39 illus : online resource |
著者標目 | *Stram, Daniel O author SpringerLink (Online service) |
件 名 | LCSH:Biometry LCSH:Medical genetics LCSH:Statistics FREE:Biostatistics FREE:Medical Genetics FREE:Statistical Theory and Methods |
一般注記 | Introduction to Genome-Wide Association Studies -- Topics of Quantitative Genetics -- An Introduction to Association Studies -- Correcting for Hidden Population Structure in Single Marker Association Testing and Estimation -- Haplotype Imputation for Association Analysis -- SNP Imputation for Association Studies -- Design of Large-scale Genetic Association Studies, Sample Size and Power -- Post-GWAS Analyses 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 HTTP:URL=https://doi.org/10.1007/978-1-4614-9443-0 |
目次/あらすじ
所蔵情報を非表示
電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
電子ブック | オンライン | 電子ブック |
|
Springer eBooks | 9781461494430 |
|
電子リソース |
|
EB00236959 |
書誌詳細を非表示
データ種別 | 電子ブック |
---|---|
分 類 | LCC:QH323.5 DC23:57,015,195 |
書誌ID | 4000120167 |
ISBN | 9781461494430 |
類似資料
この資料の利用統計
このページへのアクセス回数:1回
※2017年9月4日以降