Handbook of Statistical Genomics

David J. Balding, Ida Moltke, John Marioni

• Publisher: Wiley
• Year: 2019
• Print ISBN: 9781119429142
• eBook ISBN: 9781119429227
• Edition: 4
• Topic: Biological Sciences
• Subtopic: Genetics & Genomics
• Index: Biological Sciences

A timely update of a highly popular handbook on statistical genomics

This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation.

The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research.

• Provides much-needed, timely coverage of new developments in this expanding area of study
• Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics
• Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics
• Extensive coverage of human genetic epidemiology, including ethical aspects
• Edited by one of the leading experts in the field along with rising stars as his co-editors
• Chapter authors are world-renowned experts in the field, and newly emerging leaders.

The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.

Table of contents

• Handbook of Statistical Genomics
• Contents
• List of Contributors
• Editors’ Preface to the Fourth Edition
• Glossary
• Abbreviations and Acronyms
• 1 Statistical Modeling and Inference in Genetics
• 2 Linkage Disequilibrium, Recombination and Haplotype Structure
• 3 Haplotype Estimation and Genotype Imputation
• 4 Mathematical Models in Population Genetics
• 5 Coalescent Theory
• 6 Phylogeny Estimation Using Likelihood-Based Methods
• 7 The Multispecies Coalescent
• 8 Population Structure, Demography and Recent Admixture
• 9 Statistical Methods to Detect Archaic Admixture and Identify Introgressed Sequences
• 10 Population Genomic Analyses of DNA from Ancient Remains
• 11 Sequence Covariation Analysis in Biological Polymers
• 12 Probabilistic Models for the Study of Protein Evolution
• 13 Adaptive Molecular Evolution
• 14 Detecting Natural Selection
• 15 Evolutionary Quantitative Genetics
• 16 Conservation Genetics
• 17 Statistical Methods for Plant Breeding
• 18 Forensic Genetics
• Handbook of Statistical Genomics
• Contents
• List of Contributors
• Editors’ Preface to the Fourth Edition
• Glossary
• Abbreviations and Acronyms
• 19 Ethical Issues in Statistical Genetics
• 20 Descent-Based Gene Mapping in Pedigrees and Populations
• 21 Genome-Wide Association Studies
• 22 Replication and Meta-analysis of Genome-Wide Association Studies
• 23 Inferring Causal Relationships between Risk Factors and Outcomes Using Genetic Variation
• 24 Improving Genetic Association Analysis through Integration of Functional Annotations of the Human Genome
• 25 Inferring Causal Associations between Genes and Disease via the Mapping of Expression Quantitative Trait Loci
• 26 Statistical Methods for Single-Cell RNA-Sequencing
• 27 Variant Interpretation and Genomic Medicine
• 28 Prediction of Phenotype from DNA Variants
• 29 Disease Risk Models
• 30 Bayesian Methods for Gene Expression Analysis
• 31 Modelling Gene Expression Dynamics with Gaussian Process Inference
• 32 Modelling Non-homogeneous Dynamic Bayesian Networks with Piecewise Linear Regression Models
• 33 DNA Methylation
• 34 Statistical Methods in Metabolomics
• 35 Statistical and Computational Methods in Microbiome and Metagenomics
• 36 Bacterial Population Genomics
• Reference Author Index
• Subject Index
• EULA