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Heterogeneity in Statistical Genetic...
~
Gordon, Derek.
Heterogeneity in Statistical Genetics = How to Assess, Address, and Account for Mixtures in Association Studies /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Heterogeneity in Statistical Genetics/ by Derek Gordon, Stephen J. Finch, Wonkuk Kim.
其他題名:
How to Assess, Address, and Account for Mixtures in Association Studies /
作者:
Gordon, Derek.
其他作者:
Kim, Wonkuk.
面頁冊數:
XX, 352 p. 41 illus., 26 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Genetics and Genomics. -
電子資源:
https://doi.org/10.1007/978-3-030-61121-7
ISBN:
9783030611217
Heterogeneity in Statistical Genetics = How to Assess, Address, and Account for Mixtures in Association Studies /
Gordon, Derek.
Heterogeneity in Statistical Genetics
How to Assess, Address, and Account for Mixtures in Association Studies /[electronic resource] :by Derek Gordon, Stephen J. Finch, Wonkuk Kim. - 1st ed. 2020. - XX, 352 p. 41 illus., 26 illus. in color.online resource. - Statistics for Biology and Health,1431-8776. - Statistics for Biology and Health,.
1. Introduction to heterogeneity in statistical genetics -- 2. Overview of genomic heterogeneity in statistical genetics -- 3. Phenotypic heterogeneity -- 4. Association tests allowing for heterogeneity -- 5. Designing genetic linkage and association studies that maintain desired statistical power in the presence of mixtures -- 6. Threshold-selected quantitative trait loci and pleiotropy -- Index.
Heterogeneity, or mixtures, are ubiquitous in genetics. Even for data as simple as mono-genic diseases, populations are a mixture of affected and unaffected individuals. Still, most statistical genetic association analyses, designed to map genes for diseases and other genetic traits, ignore this phenomenon. In this book, we document methods that incorporate heterogeneity into the design and analysis of genetic and genomic association data. Among the key qualities of our developed statistics is that they include mixture parameters as part of the statistic, a unique component for tests of association. A critical feature of this work is the inclusion of at least one heterogeneity parameter when performing statistical power and sample size calculations for tests of genetic association. We anticipate that this book will be useful to researchers who want to estimate heterogeneity in their data, develop or apply genetic association statistics where heterogeneity exists, and accurately evaluate statistical power and sample size for genetic association through the application of robust experimental design.
ISBN: 9783030611217
Standard No.: 10.1007/978-3-030-61121-7doiSubjects--Topical Terms:
1229010
Genetics and Genomics.
LC Class. No.: QA276-280
Dewey Class. No.: 519.5
Heterogeneity in Statistical Genetics = How to Assess, Address, and Account for Mixtures in Association Studies /
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Heterogeneity, or mixtures, are ubiquitous in genetics. Even for data as simple as mono-genic diseases, populations are a mixture of affected and unaffected individuals. Still, most statistical genetic association analyses, designed to map genes for diseases and other genetic traits, ignore this phenomenon. In this book, we document methods that incorporate heterogeneity into the design and analysis of genetic and genomic association data. Among the key qualities of our developed statistics is that they include mixture parameters as part of the statistic, a unique component for tests of association. A critical feature of this work is the inclusion of at least one heterogeneity parameter when performing statistical power and sample size calculations for tests of genetic association. We anticipate that this book will be useful to researchers who want to estimate heterogeneity in their data, develop or apply genetic association statistics where heterogeneity exists, and accurately evaluate statistical power and sample size for genetic association through the application of robust experimental design.
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