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RT Book, Whole SR Electronic DC OPAC T1 Quantitative Genetics / by Shizhong Xu A1 Xu, Shizhong A1 SpringerLink (Online service) YR 2022 FD 2022 SP XVII, 414 p. 1 illus K1 Bioinformatics K1 Plant genetics K1 Medical genetics K1 Life sciences K1 Agricultural genome mapping K1 Bioinformatics K1 Computational and Systems Biology K1 Plant Genetics K1 Medical Genetics K1 Life Sciences K1 Agricultural Genetics ED 1st ed. 2022. PB Springer International Publishing : Imprint: Springer PP Cham SN 9783030839406 LA English (英語) CL LCC:QH324.2-324.25 CL DC23:570.285 NO Preface -- About the Author -- 1 Introduction to Quantitative Genetics -- 2 Review of Mendelian Genetics -- 3 Basic Concept of Population Genetics -- 4 Review of Elementary Statistics -- 5 Genetic Effects of Quantitative Traits -- 6 Genetic Variances of Quantitative Traits 7 Environmental Effects and Environmental Errors -- 8 Major Gene Detection and Segregation Analysis -- 9 Resemblance Between Relatives -- 10 Estimation of Heritability -- 11 Identity-by-Descent and Coancestry Coefficient -- 12 Mixed Model Analysis of Genetic Variances -- 13 Multiple Traits and Genetic Correlation Between Traits -- 14 Concept and Theory of Selection -- 15 Methods of Artificial Selection -- 16 Selection Index and Best Linear Unbiased Prediction -- 17 Methods of Multiple Trait Selection -- 18 Mapping Quantitative Trait Loci -- 19 Genome-wide Association Studies -- 20 Genomic Selection -- Index NO The intended audience of this textbook are plant and animal breeders, upper-level undergraduate and graduate students in biological and agricultural science majors. Statisticians who are interested in understanding how statistical methods are applied to genetics and agriculture can benefit substantially by reading this book. One characteristic of this textbook is represented by three chapters of technical reviews for Mendelian genetics, population genetics and preliminary statistics, which are prerequisites for studying quantitative genetics. Numerous examples are provided to illustrate different methods of data analysis and estimation of genetic parameters. Along with each example of data analyses is the program code of SAS (statistical analysis system) NO HTTP:URL=https://doi.org/10.1007/978-3-030-83940-6 NO 書誌ID=EB00002227; LK [E Book]https://doi.org/10.1007/978-3-030-83940-6 OL 30