Coverart for item
The Resource Heterogeneity in Statistical Genetics : How to Assess, Address, and Account for Mixtures in Association Studies, by Derek Gordon, Stephen J. Finch, Wonkuk Kim, (electronic resource)

Heterogeneity in Statistical Genetics : How to Assess, Address, and Account for Mixtures in Association Studies, by Derek Gordon, Stephen J. Finch, Wonkuk Kim, (electronic resource)

Label
Heterogeneity in Statistical Genetics : How to Assess, Address, and Account for Mixtures in Association Studies
Title
Heterogeneity in Statistical Genetics
Title remainder
How to Assess, Address, and Account for Mixtures in Association Studies
Statement of responsibility
by Derek Gordon, Stephen J. Finch, Wonkuk Kim
Creator
Contributor
Author
Subject
Language
eng
Summary
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.--
Member of
Assigning source
Provided by publisher
http://library.link/vocab/creatorName
Gordon, Derek
Image bit depth
0
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • Finch, Stephen J
  • Kim, Wonkuk
Series statement
  • Statistics for Biology and Health,
  • Springer eBooks.
http://library.link/vocab/subjectName
  • Statistics
  • Human genetics
  • Genetics
Label
Heterogeneity in Statistical Genetics : How to Assess, Address, and Account for Mixtures in Association Studies, by Derek Gordon, Stephen J. Finch, Wonkuk Kim, (electronic resource)
Link
https://eui.idm.oclc.org/login?url=https://doi.org/10.1007/978-3-030-61121-7
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
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
Control code
978-3-030-61121-7
Dimensions
unknown
Edition
1st ed. 2020.
Extent
1 online resource
File format
multiple file formats
Form of item
  • online
  • electronic
Isbn
9783030611217
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
Label
Heterogeneity in Statistical Genetics : How to Assess, Address, and Account for Mixtures in Association Studies, by Derek Gordon, Stephen J. Finch, Wonkuk Kim, (electronic resource)
Link
https://eui.idm.oclc.org/login?url=https://doi.org/10.1007/978-3-030-61121-7
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
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
Control code
978-3-030-61121-7
Dimensions
unknown
Edition
1st ed. 2020.
Extent
1 online resource
File format
multiple file formats
Form of item
  • online
  • electronic
Isbn
9783030611217
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote

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