Handbook of Statistical Genomics 4e
Published on 29. July 2019
Software
Other digital
1224 pages
978-1-119-48784-5 (ISBN)
Description
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.
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.
More details
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
Professional and scholarly
Dimensions
Height: 250 mm
Width: 150 mm
Thickness: 15 mm
Weight
666 gr
ISBN-13
978-1-119-48784-5 (9781119487845)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
David J. Balding | Ida Moltke | John Marioni
Handbook of Statistical Genomics
Book
09/2019
4th Edition
Wiley
€349.50
Available immediately
David J. Balding | Ida Moltke | John Marioni
Handbook of Statistical Genomics
E-Book
07/2019
4th Edition
Wiley-ISTE
€323.99
Available for download
David J. Balding | Ida Moltke | John Marioni
Handbook of Statistical Genomics
E-Book
07/2019
4th Edition
Wiley-ISTE
€323.99
Available for download
Person
DAVID J. BALDING, PhD, is Professor of Statistical Genetics at the University of Melbourne and holds an honorary appointment at University College London.
IDA MOLTKE, PhD, is an Assistant Professor at the Department of Biology, University of Copenhagen.
JOHN MARIONI, PhD, is a Group Leader at the European Bioinformatics Institute and the Cancer Research UK Cambridge Institute.
IDA MOLTKE, PhD, is an Assistant Professor at the Department of Biology, University of Copenhagen.
JOHN MARIONI, PhD, is a Group Leader at the European Bioinformatics Institute and the Cancer Research UK Cambridge Institute.
Content
Volume 1
List of Contributors.
Editor's Preface to the Fourth Edition.
Glossary of Terms.
Abbreviations and Acronyms.
1 Model based inference. Daniel Wegmann, Christoph Leuenberger (University of Freiberg)
2 Linkage disequilibrium, recombination and haplotype structure. Jerome Kelleher, Gil McVean (University of Oxford)
3 Haplotype Estimation and Genotype Imputation. Jonathan Marchini (University of Oxford)
4 Mathematical Models in Population Genetics. A Etheridge (Oxford), N Barton (IST Austria)
5 Coalescent Theory. Magnus Nordborg (Gregor Mendel Institute Vienna)
6 Phylogenetics - likelihood methods. John Huelsenbeck (Berkeley)
7 The Multi-Species Coalescent. Laura Kubatko (Ohio)
8 Population structure, demography and recent admixture. Garrett Hellenthal (UCL)
9 Ancient admixture and introgression. Liming Li, Joshua Akey (Princeton University)
10 Ancient DNA (and what it has taught us about human history). Torsten Guenther, Mattias Jakobsson (Uppsala University)
11 Protein Structure. Willie Taylor, David Jones (both Crick Institute, London)
12 Probabilistic models for the study of protein evolution. Nick Goldman (EBI), Jeff Thorne (NCSU), Ian Moal (EBI), Umberto Perron (EBI)
13 Adaptive Molecular Evolution. Ziheng Yang (UCL)
14 Detecting natural selection. Aaron Stern, Rasmus Nielsen (both Berkeley)
15 Evolutionary Quantitative Genetics. Bruce Walsh (Arizona), Michael Morrissey (St Andrews)
16 Conservation Genetics. Jinliang Wang (London Zoo Institute), Mark Beaumont (Bristol)
17 Plant breeding. Ian Mackay, (NIAB, Cambridge), Hans-Peter Piepho (Hohenheim), Augusto Garcia (Sao Paulo)
18 Forensics. Bruce Weir (U Washington, Seattle)
Author Index
Subject Index
Volume 2
List of Contributors. [as Volume 1]
Editor's Preface to the Fourth Edition. [as Volume 1]
Glossary of Terms. [as Volume 1]
Abbreviations and Acronyms. [as Volume 1]
19 Ethics. Richard Ashcroft (Queen Mary, London), Susan Wallace (Leicester)
20 Descent-based gene mapping in pedigrees and populations. Elizabeth Thompson (U Wash, Seattle)
21 Genome-wide association studies. Andrew Morris (Liverpool), Lon Cardon (GSK, USA)
22 Post-GWAS analyses. Paul Newcombe (Cambridge), Frank Dudbridge (Leicester)
23 Inferring Causality from GWAS Data. Stephen Burgess (BSU Cambridge)
24 Improving genetic association analysis through integration of functional genome annotations. Hongyu Zhao (Yale) Qiongshi Lu (University of Wisconsin-Madison)
25 Inferring Causal Associations between Genes and Disease via the Mapping of Expression Quantitative Trait Loci. Solly Sieberts and Eric Schadt (Sage Bionetworks Seattle)
26 Single-cell RNA-seq analysis. Tallulah Andrews, Vladmir Kiselev, Martin Hemberg (Sanger)
27 Variant interpretation and genomic medicine. Slave Petrovski (Astrazeneca Cambridge), David Goldstein (Columbia), Vimla Aggarwal (Columbia), Keren Carss (Astrazeneca Cambridge).
28 Prediction of phenotype from DNA polymorphisms. M Goddard (Melbourne), T Meuwissen (Oslo), H Daetwyler (Melbourne)
29 Risk Prediction Models. N Chatterjee (Johns Hopkins), Allison Meisner (U Washington)
30 Bayesian Methods for eQTL analysis. Alex Lewin (Brunel), Leonardo Bottolo (Cambridge), Sylvia Richardson (BSU)
31 Modelling gene expression dynamics with Gaussian processes. Magnus Rattray, Jing Yang, Sumon Ahmed (Manchester) and Alexis Boukouvalas (?)
32 Constructing gene regulatory networks using DBNs. Dirk Husmeier (Glasgow), Marco Grzegorczyk (Groningen)
33 Epigenetics (DNA methylation). Kasper Hansen (Johns Hopkins), Shili Lin (Ohio State) Kim Siegmund (USC)
34 Metabolomics. Tim Ebbels (Imperial), Maria De Lorio (UCL), David Stephens (McGill)
35 Microbiome and Metagenomics. Hongzhe Li (U Pennsylvania)
36 Bacterial genomics. Jukka Corander (Oslo/Helsinki), Simon Harris (Sanger), Nicholas Croucher (Imperial), John Lees (NYU), Gerry Tonkin-Hill (Cambridge)
Author Index
Subject Index
List of Contributors.
Editor's Preface to the Fourth Edition.
Glossary of Terms.
Abbreviations and Acronyms.
1 Model based inference. Daniel Wegmann, Christoph Leuenberger (University of Freiberg)
2 Linkage disequilibrium, recombination and haplotype structure. Jerome Kelleher, Gil McVean (University of Oxford)
3 Haplotype Estimation and Genotype Imputation. Jonathan Marchini (University of Oxford)
4 Mathematical Models in Population Genetics. A Etheridge (Oxford), N Barton (IST Austria)
5 Coalescent Theory. Magnus Nordborg (Gregor Mendel Institute Vienna)
6 Phylogenetics - likelihood methods. John Huelsenbeck (Berkeley)
7 The Multi-Species Coalescent. Laura Kubatko (Ohio)
8 Population structure, demography and recent admixture. Garrett Hellenthal (UCL)
9 Ancient admixture and introgression. Liming Li, Joshua Akey (Princeton University)
10 Ancient DNA (and what it has taught us about human history). Torsten Guenther, Mattias Jakobsson (Uppsala University)
11 Protein Structure. Willie Taylor, David Jones (both Crick Institute, London)
12 Probabilistic models for the study of protein evolution. Nick Goldman (EBI), Jeff Thorne (NCSU), Ian Moal (EBI), Umberto Perron (EBI)
13 Adaptive Molecular Evolution. Ziheng Yang (UCL)
14 Detecting natural selection. Aaron Stern, Rasmus Nielsen (both Berkeley)
15 Evolutionary Quantitative Genetics. Bruce Walsh (Arizona), Michael Morrissey (St Andrews)
16 Conservation Genetics. Jinliang Wang (London Zoo Institute), Mark Beaumont (Bristol)
17 Plant breeding. Ian Mackay, (NIAB, Cambridge), Hans-Peter Piepho (Hohenheim), Augusto Garcia (Sao Paulo)
18 Forensics. Bruce Weir (U Washington, Seattle)
Author Index
Subject Index
Volume 2
List of Contributors. [as Volume 1]
Editor's Preface to the Fourth Edition. [as Volume 1]
Glossary of Terms. [as Volume 1]
Abbreviations and Acronyms. [as Volume 1]
19 Ethics. Richard Ashcroft (Queen Mary, London), Susan Wallace (Leicester)
20 Descent-based gene mapping in pedigrees and populations. Elizabeth Thompson (U Wash, Seattle)
21 Genome-wide association studies. Andrew Morris (Liverpool), Lon Cardon (GSK, USA)
22 Post-GWAS analyses. Paul Newcombe (Cambridge), Frank Dudbridge (Leicester)
23 Inferring Causality from GWAS Data. Stephen Burgess (BSU Cambridge)
24 Improving genetic association analysis through integration of functional genome annotations. Hongyu Zhao (Yale) Qiongshi Lu (University of Wisconsin-Madison)
25 Inferring Causal Associations between Genes and Disease via the Mapping of Expression Quantitative Trait Loci. Solly Sieberts and Eric Schadt (Sage Bionetworks Seattle)
26 Single-cell RNA-seq analysis. Tallulah Andrews, Vladmir Kiselev, Martin Hemberg (Sanger)
27 Variant interpretation and genomic medicine. Slave Petrovski (Astrazeneca Cambridge), David Goldstein (Columbia), Vimla Aggarwal (Columbia), Keren Carss (Astrazeneca Cambridge).
28 Prediction of phenotype from DNA polymorphisms. M Goddard (Melbourne), T Meuwissen (Oslo), H Daetwyler (Melbourne)
29 Risk Prediction Models. N Chatterjee (Johns Hopkins), Allison Meisner (U Washington)
30 Bayesian Methods for eQTL analysis. Alex Lewin (Brunel), Leonardo Bottolo (Cambridge), Sylvia Richardson (BSU)
31 Modelling gene expression dynamics with Gaussian processes. Magnus Rattray, Jing Yang, Sumon Ahmed (Manchester) and Alexis Boukouvalas (?)
32 Constructing gene regulatory networks using DBNs. Dirk Husmeier (Glasgow), Marco Grzegorczyk (Groningen)
33 Epigenetics (DNA methylation). Kasper Hansen (Johns Hopkins), Shili Lin (Ohio State) Kim Siegmund (USC)
34 Metabolomics. Tim Ebbels (Imperial), Maria De Lorio (UCL), David Stephens (McGill)
35 Microbiome and Metagenomics. Hongzhe Li (U Pennsylvania)
36 Bacterial genomics. Jukka Corander (Oslo/Helsinki), Simon Harris (Sanger), Nicholas Croucher (Imperial), John Lees (NYU), Gerry Tonkin-Hill (Cambridge)
Author Index
Subject Index