The fundamentals of modern statistical genetics:
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York
Springer
[2011]
|
| Series: | Statistics for biology and health
|
| Subjects: | |
| Online Access: | Inhaltstext Inhaltsverzeichnis Klappentext |
| Item Description: | Hier auch später erschienene, unveränderte Nachdrucke |
| Physical Description: | xiv, 223 Seiten Illustrationen, Diagramme |
| ISBN: | 9781461427759 9781441973375 1441973370 |
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MARC
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Contents
1
Introduction to Statistical Genetics and Background
in Molecular Genetics
. 1
1.1
Basic Concepts in Genetic Disease
. 2
1.2
Review of Molecular Genetics
. 6
1.3
Types of Genetic Variants
. 9
1.4
Effects of Genetic Variants on Disease
. 12
2
Principles of Inheritance: Mendel's Laws and Genetic Models
. 15
2.1
Mendel's Experiments
. 15
2.2
A Framework for Genetic Models
. 19
2.3
The Biology Underlying Mendelian Inheritance
. 24
2.4
Exercises
. 28
3
Some Basic Concepts from Population Genetics
. 31
3.1
Estimation of
Alíele
Frequencies
. 31
3.2
Population Substructure
. 33
3.2.1
Population Stratification
. 33
3.2.2
Population Admixture
. 34
3.2.3
Population Inbreeding
. 35
3.3
Hardy-Weinberg Equilibrium
. 36
3.3.1
Testing for HWE
. 38
3.3.2
Some Causes of the Failure of HWE
. 39
3.3.3
Measuring the Departure from HWE
. 41
3.4
Exercises
. 42
4
Aggregation, HeritabUity and Segregation Analysis: Modeling
Genetic Inheritance Without Genetic Data
. 45
4.1
Preliminaries
. 46
4.2
Aggregation Analysis
. 48
4.2.1
Estimating Recurrence Risk Ratios
. 51
4.2.2
Further Simplifications
. 51
4.3
Heritability Analysis
. 54
Contents
4.4
Segregation Analysis
. 57
4.4.1
Segregation Analysis for Dominant Mendelian
Diseases
. 58
4.4.2
Segregation Analysis for Recessive Mendelian
Diseases
. 62
4.4.3
Summary
. 63
4.5
Exercises
. 63
5
The General Concepts of Gene Mapping: Linkage, Association,
Linkage Disequilibrium and Marker Maps
. 67
5.1
Introduction
. 67
5.2
Genetic Markers and Marker Maps
. 72
5.3
Testing for Linkage or Association: Basic Concepts
. 75
5.4
A Formal Definition of Linkage Disequilibrium and Related
Measures Used to Describe Linkage Disequilibrium
. 77
5.5
The Origin and Extent of LD in the Human Genome
. 81
5.6
The Human Genome and HapMap Projects
. 82
5.7
Exercises
. 84
6
Basic Concepts of Linkage Analysis
. 87
6.1
Basic Approach to Assessing Linkage Between Two Loci
. 88
6.2
The Direct Counting Method
. 90
6.3
The Interpretation of
LOD
Scores
. 94
6.4
Exercises
. 95
7
The Basics of Genetic Association Analysis
. 99
7.1
Testing Association with Dichotomous Disease Traits:
Codominant, Recessive and Dominant Models
. 101
7.2
The Additive Genetic Model: The
Alíeles
Test
and the Trend Test
. 103
7.3
Small Sample and Permutation Tests
.106
7.4
Which Mode of Inheritance Should We Assume for Testing?
. 107
7.5
Estimating Effect Sizes and Confidence Intervals
.108
7.6
Examples of Testing Association with Diallelic Markers
.109
7.7
The Regression Approach: Extensions to Covariate Adjustment
and to Other Phenotypes
.
Ill
7.8
Association Analysis with Complex Traits: An Association
Between INSIG2 and
BMI. 114
7.9
Sample Size and Power Considerations
for Case-Control Design
. 116
7.10
Power and Effect Estimation: Testing a Marker in LD
with the DSL
. 120
7.11
Exercises
.122
Contents xiii
8 Population
Substructure in Association Studies
.125
8.1
The Impact of Population-Admixture and Stratification
on Genetic Association Tests
. 127
8.2
Genomic Control Approaches
.132
8.3
Modeling the Effects of Population Admixture
and Stratification
. 133
8.4
Regression-Based and Principal Component Approaches
.133
8.5
Exercises
.136
9
Association Analysis in Family Designs
.139
9.1
The Trio Design and the TDT
.139
9.2
Family Based Association Tests: FBAT
.142
9.2.1
Missing Parents
.145
9.2.2
Comparative Power for Family-Based
and Case-Control Designs
. 147
9.3
Applications
.148
9.3.1
Using FBAT to Obtain the TDT
.149
9.3.2
Deriving a TDT for a Recessive Mode
of Inheritance
. 150
9.3.3
Informative Families
.150
9.3.4
Codominant Mode of Inheritance
.151
9.3.5
Multiallelic Test
.151
9.3.6
Using Unaffected Offspring
.152
9.3.7
Missing Parental Information
.153
9.3.8
Quantitative Traits
.156
9.4
Exercises
.158
10
Advanced Topics
.161
10.1
The Multiple Testing Problem in Association Studies
.161
10.1.1
Methods Based on P-Value Adjustment
.161
10.1.2
Permutation and Monte Carlo Tests
.164
10.2
Other Methods for the Analysis of Multiple SNPs,
Including Haplotypes
. 165
10.3
Gene-Environment/Gene-Drug Interaction
.170
10.4
Exercises
.174
11
Genome Wide Association Studies
.175
11.1
Introduction
.175
11.2
Quality-Control for the Genotype Data
.176
11.3
Multi-Stage Designs
.182
11.4
Testing Strategies for Family-Based Studies
.185
11.5
Replication, Non-replications and Meta-analysis
.186
11.6
Exercises
.189
xiv Contents
12
Looking Toward the Future
.191
A Basic Concepts of Linkage Analysis (Continued from Chapter
6) . 193
A.I General Issues with Parametric Linkage Analysis
.193
A.2 Non-parametric Linkage Analysis
.195
A.3 Multipoint Linkage Analysis
.199
В
A Class of Score Tests for Family Designs
.203
Properties of the Score Test
.204
Missing Parents
.205
С
The TDT Tests for Both Linkage and Association (LD)
.207
Bibliography
.211
Index
.219
Statistics for Biology and Health
Nan M. Laird
· Christoph Lange
The Fundamentals of Modern Statistical Genetics
This book covers the statistical models and methods that are used to understand hu¬
man genetics, following the historical and recent developments. Starting with Mendel's
first experiments to genome-wide association studies, the book describes how genetic
information can be incorporated into statistical models to discover disease genes. All
commonly used approaches in statistical genetics (e.g. aggregation analysis, segrega¬
tion, linkage analysis, etc), are used, but the focus of the book is modern approaches
to association analysis. Numerous examples illustrate key points throughout the text,
both of Mendelian and complex genetic disorders.
The intended audience is statisticians, biostatisticians, epidemiologists and quantita¬
tively- oriented geneticists and health scientists wanting to learn about statistical meth¬
ods for genetic analysis, whether to better analyze genetic data, or to pursue research
in methodology. A background in intermediate level statistical methods is required.
The authors include few mathematical derivations and provide exercises with a broad
range of mathematical difficulty for students with different skill levels. No background
in genetics is assumed.
Man M. Laird is a Professor of Biostatistics in the Biostatistics Department at the Harvard
School of Public Health. Dr. Laird has contributed to methodology in many different
fields, including missing data, EM-algorithm, meta-analysis, statistical genetics, and has
coauthored a book with Garrett Fitzmaurice and James Ware on applied longitudinal
analysis.
She is the recipient of many awards and prizes, including Fellow of the American
Statistical Association, the American Association for the Advancement of Science, the
Florence Nightingale Award, and the Janet Norwood Award.
Christoph Lange
is an Associate Professor in the Biostatistics Department at the Harvard
School of Public Health. Alter his PhD in Statistics at the University of Reading (UK),
he has worked extensively in the field of statistical genetics. Dr.
Lange
has been the
director of the Institute of Genome Mathematics at the University of Bonn and has
received several awards in mathematics and genetics. Dr.
Lange
is the developer of the
РЙАТ
package. |
| any_adam_object | 1 |
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| discipline | Biologie Medizin |
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| spelling | Laird, Nan M. 1943- Verfasser (DE-588)131833170 aut The fundamentals of modern statistical genetics Nan M. Laird, Christoph Lange New York Springer [2011] xiv, 223 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Statistics for biology and health Hier auch später erschienene, unveränderte Nachdrucke Genetik (DE-588)4071711-2 gnd rswk-swf Statistische Analyse (DE-588)4116599-8 gnd rswk-swf Genetik (DE-588)4071711-2 s Statistische Analyse (DE-588)4116599-8 s b DE-604 Lange, Christoph Verfasser (DE-588)1064193900 aut Erscheint auch als Online-Ausgabe 978-1-4419-7338-2 text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3495802&prov=M&dok_var=1&dok_ext=htm Inhaltstext Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020871947&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020871947&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Laird, Nan M. 1943- Lange, Christoph The fundamentals of modern statistical genetics Genetik (DE-588)4071711-2 gnd Statistische Analyse (DE-588)4116599-8 gnd |
| subject_GND | (DE-588)4071711-2 (DE-588)4116599-8 |
| title | The fundamentals of modern statistical genetics |
| title_auth | The fundamentals of modern statistical genetics |
| title_exact_search | The fundamentals of modern statistical genetics |
| title_full | The fundamentals of modern statistical genetics Nan M. Laird, Christoph Lange |
| title_fullStr | The fundamentals of modern statistical genetics Nan M. Laird, Christoph Lange |
| title_full_unstemmed | The fundamentals of modern statistical genetics Nan M. Laird, Christoph Lange |
| title_short | The fundamentals of modern statistical genetics |
| title_sort | the fundamentals of modern statistical genetics |
| topic | Genetik (DE-588)4071711-2 gnd Statistische Analyse (DE-588)4116599-8 gnd |
| topic_facet | Genetik Statistische Analyse |
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