Genome-wide association studies / edited by Davoud Torkamaneh and François Belzile. -- New York, NY : Springer, 2022. – (58.17/M592/v.2481)

Contents

Preface
Contributors
PART I  REVIEWS AND OVERVIEWS
1  Designing a Genome-Wide Association Study: Main Steps and Critical Decisions
2  Preparation and Curation of Phenotypic Datasets
3  Genotyping Platforms for Genome-Wide Association Studies: Options and Practical Considerations
4  Genome-Wide Association Study Statistical Models: A Review
5  Interpretation of Manhattan Plots and Other Outputs of Genome-Wide Association Studies
PART II  PHENOTYPIC DATA FOR GWAS
6  Preparation and Curation of Multiyear, Multilocation, Multitrait Datasets
7  Development, Preparation, and Curation of High-Throughput Phenotypic Data for Genome-Wide Association Studies: A Sample Pipeline in R
8  Preparation and Curation of Omics Data for Genome-Wide Association Studies
PART III  GENOTYPIC DATA AND ASSESSMENT OF POPULATION STRUCTURE
9  Producing High-Quality Single Nucleotide Polymorphism Data for Genome-Wide Association Studies
10  A Practical Guide to Using Structural Variants for' Genome-Wide Association Studies
11  Data Integration, Imputation, and Meta-analysis for Genome-Wide Association Studies
12  Population Structure and Relatedness for Genome-Wide Association Studies
PART IV  BIOINFORMATICS TOOLS FOR GWAS
13  Performing Genome-Wide Association Studies with Multiple Models Using GAPIT
14  Performing Genome-Wide Association Studies Using rMVP
PART V  IDENTIFICATION OF CANDIDATE GENES AND VALIDATION
15  Identification and Validation of Candidate Genes from Genome-Wide Association Studies
16  Biparental Crossing and QTL Mapping for Validation of Genome-Wide Association Studies
17  Development of Breeder-Friendly KASP Markers from Genome-Wide Association Studies Results
PART VI  CASE STUDIES
18  Mapping Major Disease Resistance Genes in Soybean by Genome-Wide Association Studies
19  GWAS Case Studies in Wheat
20  Plant Microbiome-Based Genome-Wide Association Studies
Index