Оглавление
Группа авторов. Genetic Analysis of Complex Disease
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
Genetic Analysis of Complex Diseases
List of Contributors
Foreword
1 Designing a Study for Identifying Genes in Complex Traits
Introduction
Components of a Disease Gene Discovery Study
Define Disease Phenotype
Clinical Definition
Determining that a Trait Has a Genetic Component
Identification of Datasets
Develop Study Design
Family‐Based Studies
Population‐Based Studies
Approaches for Gene Discovery
Analysis. Genomic Analysis
Statistical Analysis
Bioinformatics
Follow‐up. Variant Detection
Replication
Functional Studies
Keys to a Successful Study. Foster Interaction of Necessary Expertise
Develop Careful Study Design
References
2 Basic Concepts in Genetics
Introduction
Historical Contributions. Segregation and Linkage Analysis
Hardy–Weinberg Equilibrium
DNA, Genes, and Chromosomes. Structure of DNA
Genes and Alleles
Genes and Chromosomes
Genes, Mitosis, and Meiosis
When Genes and Chromosomes Segregate Abnormally
Inheritance Patterns in Mendelian Disease
Autosomal Recessive
Autosomal Dominant
X‐linked Inheritance
Mitochondrial Inheritance
Y‐linked
Genetic Changes Associated with Disease/ Trait Phenotypes. Mutations Versus Polymorphisms
Point Mutations
Sickle Cell Anemia
Achondroplasia
Deletion/Insertion Mutations
Duchenne and Becker Muscular Dystrophy
Cystic Fibrosis
Charcot‐Marie‐Tooth Disease
Nucleotide Repeat Disorders
Susceptibility Versus Causative Genes
Summary
References
3 Determining the Genetic Component of a Disease
Introduction
Study Design
Selecting a Study Population
Population‐Based
Clinic‐Based
Ascertainment
Single Affected Individual
Relative Pairs
Extended Families
Healthy or Unaffected Controls
Ascertainment Bias
Approaches to Determining the Genetic Component of a Disease
Co‐segregation with Chromosomal Abnormalities and Other Genetic Disorders
Familial Aggregation
Family History Approach
Example of Calculating Attributable Fraction
Correlation Coefficients
Twin and Adoption Studies
Recurrence Risk in Relatives of Affected Individuals
Heritability
Example Using Correlation Coefficients to Calculate Heritability
Segregation Analysis
Summary
References
4 Study Design for Genetic Studies
Introduction
Selecting a Study Population
Family‐Based Studies (Linkage)
Family‐Based Studies (Association)
Studies of Unrelated Individuals (Association)
Cohort Studies
Cross‐Sectional Studies
Case–Control Studies
Other Study Designs
Biobanks
Other Biobanks
Biospecimens for Biobanks
Summary
References
5 Responsible Conduct of Research in Genetic Studies
Introduction
Research Regulations and Genetics Research
Addressing Pertinent ELSI in Genetic Research. Genetic Discrimination
Privacy and Confidentiality
Certificate of Confidentiality
Coding Data and Samples
Secondary Subjects
Future Use of Samples/Data Sharing
Handling of Research Results
CLIA Regulations: Separation of Research and Clinical Laboratories
Releasing Children's Genetic Research Results
DNA Ownership
DNA Banking
Family Coercion
Practical Methods for Efficient High‐Quality Genetic Research Services
The Investigator as the Genetic Study Coordinator
Time Spent
Recruitment
Support Groups and Organizations
Referrals from Health Care Providers
Research Databases and the Internet
Institution Databases
Medical Clinics
Recruitment by Family Members
Informed Consent
Vulnerable Populations
Minors
Persons with Cognitive Impairment
Data and Sample Collection. Sample Collection
Confirmation of Diagnosis
The Art of Field Studies
Referring for Additional Medical Services
Maintaining Contact with Participants
Future Considerations
References
Note
6 Linkage Analysis
Disease Gene Discovery
Example 1 Parametric Linkage Analysis in Pedigree with Unlinked Marker
Example 2 Linkage Analysis in Pedigree with Linked Marker
Example 3 Linkage Phase Unknown
Ability to Detect Linkage
Real World Example of LOD Score Calculation and Interpretation
Disease Gene Localization
Multipoint Analysis
Effects of Misspecified Model Parameters in LOD Score Analysis
Impact of Incorrect Disease Allele Frequency
Impact of Incorrect Mode of Inheritance
Impact of Incorrect Disease Penetrance
Impact of Incorrect Marker Allele Frequency
Control of Scoring Errors
Genetic Heterogeneity
Practical Approach for Model‐Based Linkage Analysis of Complex Traits
Nonparametric Linkage Analysis
Identity by State and Identity by Descent
Methods for Nonparametric Linkage Analysis
Tests for Linkage Using Affected Sibling Pairs (ASP) Test Based on Identity by State
Tests Based on Identity by Descent in ASPs. Simple Tests
Tests Applicable When IBD Status Cannot Be Determined
Multipoint Affected Sib‐Pair Methods
Handling Sibships with More Than 2 Affected Siblings
Methods Incorporating Affected Relative Pairs
NPL Analysis
Fitting Population Parameters
Power Analysis and Experimental Design Considerations for Qualitative Traits. Factors Influencing Power of Sib‐pair Methods
The Example of Testicular Cancer
Examples of Sib‐Pair Methods for Mapping Complex Traits
Mapping Quantitative Traits
Measuring Genetic Effects in Quantitative Traits
Study Design for Quantitative Trait Linkage Analysis
Haseman–Elston Regression
Variance Components Linkage Analysis
Nonparametric Methods
The Future
Software Available
References
Note
7 Data Management
Developing a Data Organization Strategy. A Brief Overview of Data Normalization
Database Management System (DBMS) and Structured Query Language (SQL)
Partitioning Data by Type
Sequence‐Level Data
Sample‐Level Data
Database Implementation. Hardware and Software Requirements
Implementation and Performance Tuning
Interacting with the Database Directly
Security
Other Tools for Data Management and Manipulation
R
PLINK
SAMtools
Workflow Management and Cloud Computing
Conclusion
References
8 Linkage Disequilibrium and Association Analysis
Introduction
Linkage Disequilibrium
Measures of Allelic Association
Causes of Allelic Association
Mapping Genes Using Linkage Disequilibrium
Tests of Association
Case–Control Tests. Test Statistics
Measures of Disease Association and Impact
Assessing Confounding Bias
Family‐Based Tests of Association
The Transmission/Disequilibrium Test
Tests Using Unaffected Sibling Controls
Tests Using Extended Pedigrees
Regression and Likelihood‐Based Methods
Association Tests with Quantitative Traits
Analysis of Haplotype Data
Genome‐Wide Association Studies (GWAS)
Special Populations
HapMap
1000 Genomes Project
Summary
References
9 Genome‐Wide Association Studies
Introduction
Definition of GWAS
Purpose of GWAS
Design
Technologies for High‐Density Genotyping
Discrete and Quantitative Trait Analysis
Case–Control, Family‐Based, and Cohort Study Designs
Statistical Power for Association and Correction for Testing Multiple Hypotheses
Data Analysis. Quality Control on Genotyping Call Data
Initial Genotyping Quality Control
Sample‐Level Quality Control
SNP‐Level Quality Control
Software Programs for Quality Control
Population Structure
Imputation
Genetic Association Testing
Meta‐Analysis and “Mega‐Analysis”
Whole‐Genome Regression‐Based GWAS
Conclusion
References
10 Bioinformatics of Human Genetic Disease Studies
Introduction
Common Threads Genome Analysis. A Brief Note on Study Design
Data Format Manipulation
Planning for Adequate Computational Resources
Storage
Processing and Memory
Networking
Genomics in the Cloud
Processing and Analysis of Genomic Data
Array‐Based Data. DNA Arrays and High‐Throughput Genotyping
Preprocessing and Initial Quality Control
Genotype Calling
Call Efficiency
Data Cleaning and Additional Quality Control
Inferring Structural Variation From SNP‐based Array Data
A Note on Statistical Analysis and Interpretation of Results
Array‐Based Analysis of Gene Expression
Preprocessing and Quality Control
Batch Effects and Data Normalization
Differential Expression
Classification and Clustering Methods
Visualization of Expression Data
Pathway and Network Analyses
Direct Counting and Other Expression Assay Procedures
Additional Uses for Oligonucleotide Arrays
ChIP‐chip
Methyl‐chip
Site‐specific Methylation Arrays
High‐Throughput Sequencing Methods for Genomics. Introduction
High‐Throughput Sequencing for Genotype Inference
Base Calling
Base Quality Recalibration
Alignment
Variant Detection and Local Realignment Around Insertion/Deletions
Genotype Calling
Indel Calling
Quality Assessment of Genotypes
Sequence Annotation
Structural Variation Inference from High‐Throughput Sequencing Data
A Brief Note on Whole‐Genome Assembly
Expression Analysis from High‐Throughput Sequencing Data – RNA‐Seq
Base‐Calling and Foundational Preprocessing Steps
Alignment
Reconstructing the Units of Transcription
Counting Sequence Reads and Normalization
Differential Expression Analysis
Classification, Clustering, and Tertiary Analyses
Additional Assays and Analysis based on High‐Throughput Sequencing Data
ChIP‐Seq and Methylation‐based Sequences. ChIP‐seq and MeDip‐seq
Methyl‐Seq
Bioinformatics Resources
Annotation of Genomic Data
Genome Browsers as Versatile Tools
Bioinformatics Frameworks and Workflows
Crowdsourcing and Troubleshooting
Data Sharing
References
11 Complex Genetic Interactions/Data Mining/Dimensionality Reduction
Human Diseases Are Complex
Complexity of Biological Systems
Genetic Heterogeneity
Statistical and Mathematical Concepts of Complex Genetic Models
Analytic Approaches to the Detection of Complex Interactions. Linkage Analysis/Genomic Sharing
Association Analysis
Genome‐Wide Association Analysis
Conclusion
References
12 Sample Size, Power, and Data Simulation
Introduction
Sample Size and Power
Power Calculations and Simulation
Power Studies for Association Analysis
Software for Calculating Power for Association Studies, Family‐ or Population‐Based
PGA: Power for Genetic Association Analyses (Menashe et al. 2008)
Fine‐Mapping Power Calculator (Udler et al. 2010)
Quanto (Gauderman 2002, 2003)
PAWE: Power for Association with Errors (Gordon et al. 2002, 2003)
PAWE‐3D (Gordon et al. 2005)
GPC: Genetic Power Calculator (Purcell et al. 2003)
CaTS (Skol et al. 2006)
INPower (Park et al. 2010)
Software for Calculating Power for Transmission Disequilibrium Testing (TDT) and Affected Sib‐Pair Testing (ASP) GPC: Genetic Power Calculator (Purcell et al. 2003)
TDT‐PC: Transmission Disequilibrium Test Power Calculator (Chen and Deng 2001)
TDTASP (Brown 2004)
TDTPOWER (Ferreira et al. 2007)
ASP/ASPSHARE
Simulation Software for Association Study Power Assessment
Backward and Forward Model Simulations
Coalescent Model Simulation – Short Genetic Sequences. ms (Hudson 2002)
SimCoal (Laval and Excoffier2004)
CoaSIM (Mailund et al. 2005)
Larger Coalescent Simulated Models. SNPSim (Posada and Wiuf 2003)
MaCS: Markovian Coalescent Simulator (Chen et al. 2009)
Forward Model Simulations – Short Genetic Sequences. FreGene (Chadeau‐Hyam et al. 2008)
SimCoal2 (Laval and Excoffier 2004)
Forward Model Simulations – Large Genetic Sequences. EASYPOP (Balloux 2001)
SIMUPOP (Peng and Amos 2008; Peng and Kimmel 2005)
ForSim (Lambert et al. 2008)
GenomeSimla (Edwards et al. 2008)
Nemo 2.2 (Guillaume and Rougemont 2006)
Resampling Simulation Tools
HAP‐SAMPLE (Wright et al. 2007)
HAPSIMU (Zhang et al. 2008)
GWAsimulator (Li and Li 2008)
HAPGEN2 (Spencer et al. 2009; Su et al. 2011)
Software for Simulation of Phenotypic Data. Phenosim (Günther et al. 2011)
Power Simulations for Linkage Analysis
Definitions for Power Assessments for Linkage Analysis
Computer Simulation Methods for Linkage Analysis of Mendelian Disease
SIMLINK (Boehnke and Ploughman 1997)
SLINK: Simulation Program for Linkage Analysis (Ott 1989)
SUP: Slink Utility Program (Lemire 2006; Schäffer et al. 2011)
ALLEGRO (Gudbjartsson et al. 2000, 2005)
MERLIN: Multipoint Engine for Rapid Likelihood Inference (Cook Jr 2002)
SimPED (Leal et al. 2005)
Power Studies for Linkage Analysis – Complex Disease
Inclusion of Unaffected Siblings
Affected Relative Pairs of Other Types
Other Considerations
Genomic Screening Strategies: One‐Stage versus Two‐Stage Designs
Software for Designing Linkage Analysis Studies of Complex Disease. SIMLA (Bass et al. 2004; Schmidt et al. 2005)
Quantitative Traits
Extreme Discordant Pairs
Sampling Consideration for the Variance Component Method
Software for Designing Linkage Analysis Studies for Quantitative Traits. SOLAR: Sequential Oligogenic Linkage Analysis Routines (Almasy and Blangero 1998)
MERLIN: Multipoint Engine for Rapid Likelihood Inference (Cook Jr 2002)
SimuPOP (Peng and Amos 2008; Peng and Kimmel 2005)
Summary
References
Note
Index
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