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Titlebook: Genome-Wide Association Studies; Davoud Torkamaneh,Fran?ois Belzile Book 2022 The Editor(s) (if applicable) and The Author(s), under exclu

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發(fā)表于 2025-3-28 17:30:14 | 只看該作者
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發(fā)表于 2025-3-28 22:12:41 | 只看該作者
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發(fā)表于 2025-3-29 02:51:10 | 只看該作者
1064-3745 expertsThis 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
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發(fā)表于 2025-3-29 04:36:13 | 只看該作者
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發(fā)表于 2025-3-29 10:53:54 | 只看該作者
https://doi.org/10.1007/978-1-4842-4433-3 in formatting of genotype data for use with popular GWAS programs. This protocol describes how typical SV genotype data can be formatted for input to three GWAS programs commonly used by the plant genetics community: TASSEL, GAPIT, and mrMLM.
46#
發(fā)表于 2025-3-29 13:44:10 | 只看該作者
Book 2022decade 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
47#
發(fā)表于 2025-3-29 16:12:32 | 只看該作者
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發(fā)表于 2025-3-29 23:16:55 | 只看該作者
A Practical Guide to Using Structural Variants for Genome-Wide Association Studies in formatting of genotype data for use with popular GWAS programs. This protocol describes how typical SV genotype data can be formatted for input to three GWAS programs commonly used by the plant genetics community: TASSEL, GAPIT, and mrMLM.
49#
發(fā)表于 2025-3-30 03:52:24 | 只看該作者
Klassifizierung der Quantenmechanik,n crops with simple genomes to crops with very complex, large, polyploid genomes. Depending on the crop and the goal of the GWAS, there are several options and practical considerations to take into account when selecting a genotyping technology to ensure that the right coverage, accuracy, and cost for the study is achieved.
50#
發(fā)表于 2025-3-30 07:35:15 | 只看該作者
https://doi.org/10.1007/978-1-4842-3643-7 as possible any effect that can lead to misestimation of the phenotypic values. The purpose of this chapter is to explain a series of important steps to explore and analyze data from METs used to characterize an association panel. Two datasets are used to illustrate two different scenarios.
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