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020 _a9781071622377
_9978-1-0716-2237-7
024 7 _a10.1007/978-1-0716-2237-7
_2doi
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082 0 4 _a581.35
_223
245 1 0 _aGenome-Wide Association Studies
_h[electronic resource] /
_cedited by Davoud Torkamaneh, François Belzile.
250 _a1st ed. 2022.
264 1 _aNew York, NY :
_bSpringer US :
_bImprint: Humana,
_c2022.
300 _aXIII, 371 p. 81 illus., 73 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aMethods in Molecular Biology,
_x1940-6029 ;
_v2481
505 0 _aDesigning a Genome-Wide Association Study: Main Steps and Critical Decisions -- Preparation and Curation of Phenotypic Datasets -- Genotyping Platforms for Genome-Wide Association Studies: Options and Practical Considerations -- Genome-Wide Association Study Statistical Models: A Review -- Interpretation of Manhattan Plots and Other Outputs of Genome-Wide Association Studies -- Preparation and Curation of Multi-Year, Multi-Location, Multi-Trait Datasets -- Development, Preparation, and Curation of High-Throughput Phenotypic Data for Genome-Wide Association Studies: A Sample Pipeline in R -- Preparation and Curation of Omics Data for Genome-Wide Association Studies -- Producing High-Quality Single Nucleotide Polymorphism Data for Genome-Wide Association Studies -- A Practical Guide to Using Structural Variants for Genome-Wide Association Studies -- Data Integration, Imputation, and Meta-Analysis for Genome-Wide Association Studies -- Population Structure and Relatedness for Genome-Wide AssociationStudies -- Performing Genome-Wide Association Studies with Multiple Models Using GAPIT -- Performing Genome-Wide Association Studies Using rMVP -- Identification and Validation of Candidate Genes from Genome-Wide Association Studies -- Biparental Crossing and QTL Mapping for Genome-Wide Association Studies Validation -- Development of Breeder Friendly KASP Markers from Genome-Wide Association Studies Results -- Mapping Major Disease Resistance Genes in Soybean by Genome-Wide Association Studies -- GWAS Case Studies in Wheat -- Plant Microbiome-Based Genome-Wide Association Studies.
520 _aThis detailed collection explores genome-wide association studies (GWAS), which have revolutionized the investigation of complex traits over the past decade and have unveiled numerous useful genotype–phenotype associations in plants. The book describes the key concepts and methods underlying GWAS, including the genetic architecture underlying variation for phenotypic traits, the structure of genetic variation in plants, technologies for capturing genetic information, study designs, and the statistical models and bioinformatics tools used for data analysis. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of invaluable implementation advice that leads to the most fruitful research results. Authoritative and practical, Genome-Wide Association Studies serves as an extremely valuable resource for the plant research community by rendering GWAS analysis less challenging and more accessible to a broader group of users.
650 0 _aPlant genetics.
650 0 _aGenomics.
650 0 _aBioinformatics.
650 1 4 _aPlant Genetics.
650 2 4 _aGenomics.
650 2 4 _aBioinformatics.
700 1 _aTorkamaneh, Davoud.
_eeditor.
_0(orcid)0000-0002-9782-5695
_1https://orcid.org/0000-0002-9782-5695
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aBelzile, François.
_eeditor.
_0(orcid)0000-0001-6893-4529
_1https://orcid.org/0000-0001-6893-4529
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9781071622360
776 0 8 _iPrinted edition:
_z9781071622384
776 0 8 _iPrinted edition:
_z9781071622391
830 0 _aMethods in Molecular Biology,
_x1940-6029 ;
_v2481
856 4 0 _uhttps://doi.org/10.1007/978-1-0716-2237-7
912 _aZDB-2-PRO
999 _c5555
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