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
Volume 1
List of Contributors xxiii
Editors’ Preface to the Fourth Edition xxvii
Glossary xxix
Abbreviations and Acronyms xxxix
1 Statistical Modeling and Inference in Genetics 1
Daniel Wegmann and Christoph Leuenberger
2 Linkage Disequilibrium, Recombination and Haplotype Structure 51
Gil McVean and Jerome Kelleher
3 Haplotype Estimation and Genotype Imputation 87
Jonathan Marchini
4 Mathematical Models in Population Genetics 115
Nick Barton and Alison Etheridge
5 Coalescent Theory 145
Magnus Nordborg
6 Phylogeny Estimation Using Likelihood-Based Methods 177
John P. Huelsenbeck
7 The Multispecies Coalescent 219
Laura Kubatko
8 Population Structure, Demography and Recent Admixture 247
G. Hellenthal
9 Statistical Methods to Detect Archaic Admixture and Identify Introgressed Sequences 275
Liming Li and Joshua M. Akey
10 Population Genomic Analyses of DNA from Ancient Remains 295
Torsten Gunther and Mattias Jakobsson
11 Sequence Covariation Analysis in Biological Polymers 325
William R. Taylor, Shaun Kandathil, and David T. Jones
12 Probabilistic Models for the Study of Protein Evolution 347
Umberto Perron, Iain H. Moal, Jeffrey L. Thorne, and Nick Goldman
13 Adaptive Molecular Evolution 369
Ziheng Yang
14 Detecting Natural Selection 397
Aaron J. Stern and Rasmus Nielsen
15 Evolutionary Quantitative Genetics 421
Bruce Walsh and Michael B. Morrissey
16 Conservation Genetics 457
Mark Beaumont and Jinliang Wang
17 Statistical Methods for Plant Breeding 501
Ian Mackay, Hans-Peter Piepho, and Antonio Augusto Franco Garcia
18 Forensic Genetics 531
B.S.Weir
Volume 2
19 Ethical Issues in Statistical Genetics 551
Susan E. Wallace and Richard Ashcroft
20 Descent-Based Gene Mapping in Pedigrees and Populations 573
E.A. Thompson
21 Genome-Wide Association Studies 597
Andrew P. Morris and Lon R. Cardon
22 Replication and Meta-analysis of Genome-Wide Association Studies 631
Frank Dudbridge and Paul Newcombe
23 Inferring Causal Relationships between Risk Factors and Outcomes Using Genetic Variation 651
Stephen Burgess, Christopher N. Foley, and Verena Zuber
24 Improving Genetic Association Analysis through Integration of Functional Annotations of the Human Genome 679
Qiongshi Lu and Hongyu Zhao
25 Inferring Causal Associations between Genes and Disease via the Mapping of Expression Quantitative Trait Loci 697
Solveig K. Sieberts and Eric E. Schadt
26 Statistical Methods for Single-Cell RNA-Sequencing 735
Tallulah S. Andrews, Vladimir Yu. Kiselev, and Martin Hemberg
27 Variant Interpretation and Genomic Medicine 761
K. Carss, D. Goldstein, V. Aggarwal, and S. Petrovski
28 Prediction of Phenotype from DNA Variants 799
M.E. Goddard, T.H.E. Meuwissen, and H.D. Daetwyler
29 Disease Risk Models 815
Allison Meisner and Nilanjan Chatterjee
30 Bayesian Methods for Gene Expression Analysis 843
Alex Lewin, Leonardo Bottolo, and Sylvia Richardson
31 Modelling Gene Expression Dynamics with Gaussian Process Inference 879
Magnus Rattray, Jing Yang, Sumon Ahmed, and Alexis Boukouvalas
32 Modelling Non-homogeneous Dynamic Bayesian Networks with Piecewise Linear Regression Models 899
Marco Grzegorczyk and Dirk Husmeier
33 DNA Methylation 933
Kasper D. Hansen, Kimberly D. Siegmund, and Shili Lin
34 Statistical Methods in Metabolomics 949
Timothy M.D. Ebbels, Maria De Iorio, and David A. Stephens
35 Statistical and Computational Methods in Microbiome and Metagenomics 977
Hongzhe Li
36 Bacterial Population Genomics 997
Jukka Corander, Nicholas J. Croucher, Simon R. Harris, John A. Lees, and Gerry Tonkin-Hill
Reference Author Index 1021
Subject Index 1109
