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  • 1
    UID:
    b3kat_BV047093609
    Format: 1 Online-Ressource (XX, 352 p. 41 illus., 26 illus. in color)
    Edition: 1st ed. 2020
    ISBN: 9783030611217
    Series Statement: Statistics for Biology and Health
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-61120-0
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-61122-4
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-61123-1
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 2
    UID:
    almahu_9948621870602882
    Format: XX, 352 p. 41 illus., 26 illus. in color. , online resource.
    Edition: 1st ed. 2020.
    ISBN: 9783030611217
    Series Statement: Statistics for Biology and Health,
    Content: 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.
    Note: 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.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9783030611200
    Additional Edition: Printed edition: ISBN 9783030611224
    Additional Edition: Printed edition: ISBN 9783030611231
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    UID:
    gbv_1743801335
    Format: 1 Online-Ressource(XX, 352 p. 41 illus., 26 illus. in color.)
    Edition: 1st ed. 2020.
    ISBN: 9783030611217
    Series Statement: Statistics for Biology and Health
    Content: 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.
    Content: 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.
    Additional Edition: ISBN 9783030611200
    Additional Edition: ISBN 9783030611224
    Additional Edition: ISBN 9783030611231
    Additional Edition: Erscheint auch als Druck-Ausgabe Gordon, Derek Heterogeneity in statistical genetics Cham : Springer, 2020 ISBN 9783030611231
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030611224
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030611231
    Language: English
    Subjects: Biology
    RVK:
    URL: Cover
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  • 4
    UID:
    edoccha_BV047093609
    Format: 1 Online-Ressource (XX, 352 p. 41 illus., 26 illus. in color).
    Edition: 1st ed. 2020
    ISBN: 978-3-030-61121-7
    Series Statement: Statistics for Biology and Health
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-61120-0
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-61122-4
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-61123-1
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    UID:
    edocfu_BV047093609
    Format: 1 Online-Ressource (XX, 352 p. 41 illus., 26 illus. in color).
    Edition: 1st ed. 2020
    ISBN: 978-3-030-61121-7
    Series Statement: Statistics for Biology and Health
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-61120-0
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-61122-4
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-61123-1
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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