Design, analysis, and interpretation of genome-wide association scans:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York, NY [u.a.]
Springer
2014
|
| Schriftenreihe: | Statistics for biology and health
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | XV, 334 S. Ill., graph. Darst. |
| ISBN: | 9781461494423 |
Internformat
MARC
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| 020 | |a 9781461494423 |9 978-1-4614-9442-3 | ||
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| 100 | 1 | |a Stram, Daniel O. |e Verfasser |0 (DE-588)170890082 |4 aut | |
| 245 | 1 | 0 | |a Design, analysis, and interpretation of genome-wide association scans |c Daniel O. Stram |
| 264 | 1 | |a New York, NY [u.a.] |b Springer |c 2014 | |
| 300 | |a XV, 334 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Statistics for biology and health | |
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| 856 | 4 | 2 | |m Digitalisierung UB Regensburg - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027522230&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |3 Klappentext |
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Datensatz im Suchindex
| _version_ | 1804152532575977472 |
|---|---|
| adam_text | Contents
1
Introduction
..........................................
j
1.1
Historical Perspective
................................ 1
1.2 DNA
Basics
.......................................
З
1.2.1
Organization of Chromosomes
.................... 3
1.2.2
Organization of
DNA........................... 4
1.2.3 DNA
and Protein
.............................. 5
1
.3
Types of Genetic Variation
............................ 6
í
.3.1
Single-Nueleotide Variants and Polymorphisms
....... 6
1.3.2
Insertions/Deletions
............................ 11
1.3.3
Larger Structural Variants
....................... 11
1.3.4
Exonic Variation and Disease
..................... 12
t
.3.5
Non-exonic SNPs and Disease
.................... 12
1.3.6
SNP Haplotypes
.............................. 13
1.3.7
Microsatellites
................................ 13
1.3.8
Mitochondrial Variation
......................... 14
Î.4
Overview of Genotyping Methods
....................... 14
1.4.1
SNP
Calling
................................. 16
1.5
Overview of
G
WAS Genotype Arrays
.................... 18
1.6
Software and Data Resources
.......................... 18
1.7
Web Resources
..................................... 19
1.7.1
Basic Genomics
............................... 19
1.7.2
GWAS Associations
........................... 20
1.7.3
Annotation
.................................. 20
1
.8
Hardware and Operating Systems
....................... 22
1.9
Data Example
...................................... 23
1.9.1
Save Your Work
.............................. 24
References
............................................ 27
2
Topics in Quantitative Genetics
........................... 31
2.Í
Distribution
of a Single Dialleiic Variant
in a Randomly Mixing Population
....................... 32
Contents
2.1.1
Hardy—
Weinberg
Equilibrium
.................... 32
2.1.2
Random Samples of Unrelated Individuals
.......... 33
2.1.3
Joint Distribution Between Relatives
of
Alíele
Counts for a Single
SNP
................ 33
2.1.4
Coefficients of Kinship and of Inbreeding
........... 36
2.2
Relationship Between Identity by State and Identity
by Descent for a Single Diallelic Marker
................. 37
2.3
Estimating IBD Probabilities from Genotype Data
.......... 38
2.4
The Covariance Matrix for a Single
Alíele
in Nonrandomly Mixing Populations
.................... 39
2.4.1
Hidden Structure and Correlation
................. 39
2.4.2
Effects of Incomplete Admixture on the
Covariance Matrix of a Single Variant
............. 42
2.5
Direct Estimation of Differentiation Parameter
F
from Genotype Data
................................ 42
2.5.1
Relatedness Revisited
......................... 43
2.5.2
Estimation of
Alíele
Frequencies
................. 45
2.6
Alíele
Frequency Distributions
........................ 45
2.6.1
Initial Mutations and Common Ancestors
........... 45
2.6.2
Mutations and the Coalescent
.................... 48
2.6.3
Allelic Distribution of Genetic Variants
............ 48
2.6.4
Alíele
Distributions Under Population
Increase and Selection
......................... 51
2.7
Recombination and Linkage Disequilibrium
............... 52
2.7.1
Quantification of Recombination
................. 54
2.7.2
Phased Versus Unphased Data and LD Estimation
..... 56
2.7.3
Hidden Population Structure
..................... 57
2.7.4
Pseudo-LD Induced by Hidden Structure
and Relatedness
.............................. 60
2.8
Covering the Genome for Common
Alíeles
............... 62
2.8.
1 High-Throughput Sequencing
.................... 65
2.9
Principal Components Analysis
........................ 65
2.9.1
Display of Principal Components
for the HapMap Phase
3
Samples
................. 67
2.10
Chapter Summary
.................................. 72
Data and Software Exercises
............................... 74
References
............................................ 75
An Introduction to Association Analysis
..................... 79
3.1
Single Marker Associations
........................... 79
3.1.1
Dominant, Recessive, and Co-dominant Effects
....... 80
3.2
Regression Analysis and Generalized Linear
Models in Genetic Analysis
........................... 82
3.3
Tests of Hypotheses for Genotype Data Using
Generalized Linear Models
........................... 84
Contents xi
3.3.1 Test
of Hypothesis regarding Genotype
Effects Testing Using Logistic Regression
in Case-Control Analysis
....................... 85
3.3.2
Interpreting Regression Equation Coefficients
........ 88
3.4
Summary of Maximum Likelihood Estimation.
Wald
Tests, Likelihood Ratio Tests. Score Tests.
and Sufficient Statistics
.............................. 90
3.4.1
Properties of Log Likelihood Functions
............. 91
3.4.2
Score Tests
................................. 93
3.4.3
Likelihood Ratio Tests
......................... 94
3.4.4 Wald
Tests
................................. 95
3.4.5
Fisher s Scoring Procedure for Finding the
M LE......
95
3.4.6
Scores and Information for Normal
and Binary Regression
......................... 96
3.4.7
Score Tests of
β
= 0
for Linear
and Logistic Models
.......................... 98
3.4.8
Matrix Formulae for Estimators
in OLS Regression
............................ 100
3.5
Covariates, Interactions, and Confounding
................ 102
3.6
Conditional Logistic Regression
....................... 104
3.6.1
Breaking the Matching in Logistic Regression
of Matched Data
............................. 105
3.6.2
Parent Affected-Offspring Design
................. 109
3.7
Case-Only Analyses
................................
Ill
3.7.1
Case-Only Analyses of Disease Subtype
............
Ill
3.7.2
Case-Only Analysis of Gene
χ
Environment
and Gene
χ
Gene Interactions
...................
Ill
3.8
Non-independent Phenotypes
......................... 114
3.8.
ί
OLS Estimation When Phenotypes
Are Correlated
............................... 114
3.9
Needs of a GWAS Analysis
.......................... 115
3.9.1
Hardware Requirements for GWAS
...............
Π
6
3.9.2
Software Solutions
............................ 116
3.10
The Multiple Comparisons Problem
..................... 118
3.11
Behavior of the Bonferroni Correction
with Non-independent Tests
.......................... 119
3.12
Reliability of Small
/7-
Values
.........................
Ш
3.12.1
Test of a Single Binomial Proportion
............. 122
3.12.2
Test of a Difference in Binomial Proportions
........ 124
3.13
Chapter Summary
.................................. 125
Appendix
............................................. 130
References
............................................ 131
xii Contents
4
Correcting for Hidden Population Structure in Single Marker
Association Testing and Estimation
........................ 135
4.1
Effects of Hidden Population Structure on the
Behavior of Statistical Tests for Association
............... 136
4.1.1
Effects on Inference Induced by Correlated
Phenotypes
.................................. 136
4.1.2
Influences of Latent Variables
.................... 140
4.1.3
Hidden Structure as a Latent Variable
............... 140
4.1.4
Polygenes, Latent Structure, Hidden Relatedness,
and Confounding
.............................. 141
4.1.5
Hidden Non-mixing Strata
....................... 142
4.1.6
Admixture
................................... 147
4.1.7
Polygenes and Cryptic Relatedness
................. 150
4.2
Correcting for the Effects of Hidden Structure
and Relatedness
.................................... 154
4.2.1
Genomic Control
.............................. 154
4.2.2
Regression-based Adjustment for Leading
Principal Components
.......................... 156
4.2.3
Implementation of Principal Components
Adjustment Methods
........................... 157
4.2.4
Random Effects Models
......................... 162
4.2.5
Retrospective Methods
.......................... 166
4.3
Comparison of Correction Methods by Simulation
........... 170
4.3.1
Comparison of the Mixed Model and Retrospective
Approach for Binary (case—control) Outcomes
........ 171
4.3.2
Conclusions
..................................
І72
4.4
Behavior of the Genomic Control Parameter
as Sample Size increases
.............................. 173
4.5
Removing Related Individuals as Part of Quality
Control, Is It Needed?
................................ 176
4.6
Chapter Summary
................................... 177
Data and Software Exercises
............................... 179
References
............................................ 179
5
Haplotype Imputation for Association Analysis
............... 183
5.1
The Role of Haplotypes in Association Testing
............. 184
5.2
Haplotypes, LD Blocks, and Haplotype Uncertainty
.......... 185
5.3
Haplotype Frequency Estimation and Imputation
............ 185
5.3.1
Small Numbers of SNPs
......................... 185
5.3.2
Haplotype Uncertainty
.......................... 186
5.4
Haplotype Frequency Estimation for Larger Numbers
of SNPs
.......................................... 190
5.4.1
Partition-Ligation EM Algorithm
.................. 190
5.4.2
Phasing Large Numbers of SNPs
.................. 190
Contents xiii
5.5 Regression
Analysis Using Haplotypes
as Explanatory Variables
............................. 191
5.5.1
Expectation Substitution
........................ 191
5.5.2
Fitting Dominant, Recessive, or Two Degrees
of Freedom Models for the Effect of Haplotypes
...... 193
5.6
Dealing with Uncertainty in Haplotype Estimation
in Association Testing
............................... 195
5.6.1
Full Likelihood Estimation of Risk Parameters
and Haplotype Frequencies
...................... 195
5.6.2
Ascertainment in Case-Control Studies
............. 197
5.6.3
Example: Expectation-Substitution Method
.......... 198
5.7
Haplotype Analysis Genome-Wide
..................... 201
5.7.1
Studies of Homogeneous Non-admixed
Populations
................................. 20
J
5.7.2
The Four-Gamete Rule for Fast Block Definition
...... 202
5.7.3
Multiple Comparisons in Haplotype Analysis
........ 204
5.8
Multiple Populations
................................ 205
5.9
Chapter Summary
.................................. 207
References
............................................ 209
6
SNP
Imputation for Association Studies
..................... 213
6.1
The Role of Imputed SNPs in Association Testing
.......... 214
6.2
EM Algorithm and
SNP
Imputation
..................... 214
6.3
Phasing Large Numbers of SNPs
for the Reference Panel
.............................. 217
6.4
Brief Introduction to Hidden Markov Models
.............. 217
6.4.1
The Baum-Welch Algorithm
................... 220
6.5
Large-Scale Imputation Using HMMs
................... 222
6.6
Using an
HMM
to Impute Missing Genotype
Data when Both the Reference Panel and Study
Genotypes Are Phased
.............................. 223
6.7
Using an
HMM
to Phase Reference or Main
Study Genotypes
................................... 229
6.7.1
Initializing and Updating the Current
List of Haplotypes
........................... 232
6.8
Practical issues in Large-Scale
SNP
Imputation
............ 235
6.8.1
Assessing Imputation Accuracy
................. 236
6.8.2
Imputing Rare SNPs
.......................... 237
6.8.3
Use of Cosmopolitan Reference Panels
............ 238
6.9
Estimating Relative Risks for Imputed SNPs
.............. 239
6.9.1
Expectation Substitution
....................... 239
6.10
Chapter Summary
.................................. 239
6.10.Í
Links
..................................... 241
References
............................................ 241
xiv Contents
7 Design
of Large-Scale Genetic Association Studies,
Sample Size, and Power
................................. 243
7.1
Design Considerations
............................... 243
7.2
Sample Size and Power for Studies of Unrelated Subjects
...... 244
7.2.1
Power for Chi-Square Tests
...................... 244
7.2.2
Calculation of Non-centrality Parameters
for Chi-Square Tests in Generalized
Linear Models
................................ 248
7.3
QUANTO
........................................ 255
7.3.1
Use of
QUANTO
to Compute Power to
Detect Main Effects of Genetic Variants
in Case-Control Studies
......................... 258
7.4
Alternative Designs
................................. 258
7.4.1
Sibling Controls
.............................. 260
7.4.2
Power for Interactions
.......................... 261
7.4.3
Parent-Affected-Offspring Trios
................... 262
7.4.4
Power for Case-Only Analysis of interactions
......... 262
7.5
Control for Multiple Comparisons
....................... 264
7.5.1
Single Marker Associations
...................... 264
7.5.2
More Complex Marker Associations
................ 264
7.5.3
Reliability of Very Small p- Values
................. 266
7.6
Two-Staged Genotyping Designs
........................ 266
7.6.1
Measured
SNP
Association Tests
.................. 267
7.6.2
Optimal Two-Stage Case-Control Designs
........... 270
7.7
Control of Population Stratification: Effects on Study Power
.... 272
7.7.1
Genomic Inflation and Study Power
................ 273
7.7.2
Correction for Admixture and Hidden Structure
by Principal Components
........................ 274
7.7.3
A Retrospective Analysis of Study Power
............ 275
7.8
Power of Multi-SNP Conditional Tests
................... 280
7.9
Chapter Summary
................................... 280
References
............................................ 283
8
Post-GWAS Analyses
................................... 285
8.1
Meta-analysis
...................................... 285
8.2
Meta-analysis of Linear or Logistic Regression Estimates
...... 287
8.2.
і
Random Effects Models
......................... 290
8.3
Meta-analysis for the
G
W
AS Setting
..................... 291
8.3.1
Meta-analysis and Imputation
..................... 292
8.4
Efficiency of Meta-analysis Versus Pooled Analysis
.......... 293
8.5
Sources of Heterogeneity in Meta-analysis of GWAS Data
..... 295
8.5.1
LD Differences
............................... 295
8.5.2
Exposure Differences
........................... 296
8.5.3
Gene
x
Gene Interactions
....................... 296
Contents xv
8.6 Meta-analysis
Based on Effect sizes. Z-scores,
and /»-Values
..................................... 297
8.6.1
Z-Score Analysis
............................ 297
8.6.2
Fisher s Method of Combining P-Values
........... 298
8.6.3
Meta-analysis of Score Tests
................... 299
8.7
Multiethnic Analyses
............................... 299
8.8
Fine Mapping of Single-SNP Associations:
Conditional Analyses
............................... 301
8.9
Fine Mapping in Admixed Populations
.................. 303
8.9.1
The Role of Local Ancestry Adjustment
........... 304
8.10
Polygenes and Heritability
........................... 305
8.10.1
Fraction of Familial Risk Explained
by a Polygene Under a Multiplicative Model
........ 305
8.10.2
Synergies Between Polygenes
and Environmental Variables
................... 306
8.11
GWAS Heritability Analysis
.......................... 306
8.11.1
Heritability Estimation in the Presence
of Population Stratification
..................... 308
8.12
Analysis of Rare Variants
............................ 309
8.13
Contribution of Rare SNPs to Phenotypic Variance
and Heritability Under a Poly genie (Additive) Model
........ 310
8.14
Moderately Rare Single-SNP Analysis
................... 312
8.15
Burden and Pathway Analysis
......................... 314
8.15.1
A Weighted Sum Statistic
...................... 315
8.15.2
Omnibus Tests. Variance Components,
and Kernel Machines
.........................
3J6
8.16
Final Remarks
.................................... 319
8.17
Chapter Summary
.................................. 321
References
............................................ 324
Index
................................................... 329
Statistics
for Biology and Health
Daniel
0.
Stra
m
Design, Analysis, and Interpretation of Genome-Wide Association
Scans
Ibis book present»
tibe
statistical aspects of designing» analyzing and interpreting
the «¿nits of genome-wide
association
scans (GWAS studies) for genetic causes of
ftteiie using unrelated subjects,
lhe
good in writing this book is to give statisticians,
epidemiologists, and students in these fields the tools needed to design and analyze
powerful genome-wide studies based on current technology. Attention is given to the
practical aspects of employing the bioinfbrmatics and data handling methods necessary
to
prepere data
for statistical analysis.
Design» Analysis and Interpretation 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 genotyping technology is quickly changing, this text has significant
lessons for future work with genome-wide 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 the extensive databases
from future, large-scale sequencing projects.
|
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| bvnumber | BV042081155 |
| classification_rvk | WC 4460 |
| ctrlnum | (OCoLC)892637132 (DE-599)BVBBV042081155 |
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| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 610 - Medicine and health |
| dewey-raw | 610 |
| dewey-search | 610 |
| dewey-sort | 3610 |
| dewey-tens | 610 - Medicine and health |
| discipline | Biologie Medizin |
| format | Book |
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| id | DE-604.BV042081155 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T01:12:13Z |
| institution | BVB |
| isbn | 9781461494423 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027522230 |
| oclc_num | 892637132 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR |
| owner_facet | DE-355 DE-BY-UBR |
| physical | XV, 334 S. Ill., graph. Darst. |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | Springer |
| record_format | marc |
| series2 | Statistics for biology and health |
| spelling | Stram, Daniel O. Verfasser (DE-588)170890082 aut Design, analysis, and interpretation of genome-wide association scans Daniel O. Stram New York, NY [u.a.] Springer 2014 XV, 334 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Statistics for biology and health Genkartierung (DE-588)4123274-4 gnd rswk-swf Genkartierung (DE-588)4123274-4 s DE-604 Erscheint auch als Online-Ausgabe 978-1-4614-9443-0 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027522230&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027522230&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Stram, Daniel O. Design, analysis, and interpretation of genome-wide association scans Genkartierung (DE-588)4123274-4 gnd |
| subject_GND | (DE-588)4123274-4 |
| title | Design, analysis, and interpretation of genome-wide association scans |
| title_auth | Design, analysis, and interpretation of genome-wide association scans |
| title_exact_search | Design, analysis, and interpretation of genome-wide association scans |
| title_full | Design, analysis, and interpretation of genome-wide association scans Daniel O. Stram |
| title_fullStr | Design, analysis, and interpretation of genome-wide association scans Daniel O. Stram |
| title_full_unstemmed | Design, analysis, and interpretation of genome-wide association scans Daniel O. Stram |
| title_short | Design, analysis, and interpretation of genome-wide association scans |
| title_sort | design analysis and interpretation of genome wide association scans |
| topic | Genkartierung (DE-588)4123274-4 gnd |
| topic_facet | Genkartierung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027522230&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027522230&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT stramdanielo designanalysisandinterpretationofgenomewideassociationscans |