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Books on the topic 'Plant population genetics Statistical methods'

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Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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1

Statistical genetics. New York: Wiley, 1993.

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2

Prem, Narain. Statistical genetics. New York: Wiley, 1990.

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3

J, Balding D., Bishop M. J, and Cannings C. 1942-, eds. Handbook of statistical genetics. 3rd ed. Chichester, England: John Wiley & Sons, 2007.

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4

Genetic data analysis: Methods for discrete population genetic data. Sunderland, Mass: Sinauer Associates, 1990.

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5

1943-, Weir B. S., ed. Interpreting DNA evidence: Statistical genetics for forensic scientists. Sunderland, Mass: Sinauer Associates, 1998.

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6

Foulkes, Andrea S. Applied statistical genetics with R: For population-based association studies. New York: Springer Verlag, 2009.

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7

Applied statistical genetics with R: For population-based association studies. New York: Springer Verlag, 2009.

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8

Foulkes, Andrea S. Applied statistical genetics with R: For population-based association studies. New York: Springer Verlag, 2009.

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9

Weir, B. S. Genetic data analysis II: Methods for discrete population genetic data. Sunderland, Mass: Sinauer Associates, 1996.

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10

Potapov, V. A. Biometrii︠a︡ plodovykh kulʹtur. Michurinsk: Michurinskiĭ gos. agrarnyĭ universitet, 2004.

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11

J, Balding D., Bishop M, and Cannings C. 1942-, eds. Handbook of statistical genetics. Chichester: Wiley, 2001.

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12

Mariotti, Jorge A. Fundamentos de genética biométrica: Aplicaciones al mejoramiento genético vegetal. Washington, D.C: Secretaría General de la Organización de los Estados Americanos, Programa Regional de Desarrollo Científico y Tecnológico, 1986.

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13

J, Balding D., Bishop M, and Cannings C. 1942-, eds. Handbook of statistical genetics. 2nd ed. Chichester, West Sussex, England: John Wiley & Sons, 2003.

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14

(2001), Ecole d'été de probabilités de Saint-Flour. Lectures on probability theory and statistics: Ecole d'été de probabilités de Saint-Flour XXXI, 2001. Berlin: Springer, 2004.

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15

I, Aksenovich T., Babenko V. N, and Borodin P. M, eds. Proverka raspredelenii͡a︡ Khardi-Vaĭnberga: Analiz kriteriev. Novosibirsk: In-t t͡s︡itologii i genetiki SO AN SSSR, 1990.

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16

Pedigree analysis in human genetics. Baltimore: Johns Hopkins University Press, 1986.

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17

Campbell, Robert Kenneth. Genetic variation and seed zones of douglas-fir in the Siskiyou National Forest. Portland, Or. (333 S.W. First Ave., P.O. Box 3890, Portland 97208): U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 1993.

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18

Ecole d'été de probabilités de Saint-Flour (2001). Lectures on probability theory and statistics: Ecole d'été de probabilités de Saint-Flour XXXI, 2001. Edited by Tavaré Simon, Zeitouni Ofer, and Picard Jean 1959-. Berlin: Springer, 2004.

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19

Christie, B. R. The diallel cross: Its analysis and interpretation. Guelph, Ont: University of Guelph, 1988.

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20

S, Kang Manjit, ed. GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. Boca Raton, Fla: CRC Press, 2003.

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21

1955-, Banzhaf Wolfgang, and Eeckman Frank H, eds. Evolution and biocomputation: Computational models of evolution. Berlin: Springer, 1995.

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22

Basford, Kaye E. Graphical analysis of multiresponse data: Illustrated with a plant breeding trial. Boca Raton, Fla: Chapman & Hall/CRC, 1999.

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23

Basford, Kaye E. Graphical analysis of multiresponse data: Illustrated with a plant breeding trial : interdisciplinary statistics. Boca Raton, Fla: Chapman & Hall/CRC, 1999.

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24

author, Sarich Marco 1985, ed. Metastability and Markov state models in molecular dynamics: Modeling, analysis, algorithmic approaches. Providence, Rhode Island: American Mathematical Society, 2013.

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25

Capretti, Paolo, Cecilia Comparini, Matteo Garbelotto, and Nicola La Porta, eds. XIII Conference "Root and Butt Rot of Forest Trees" IUFRO Working Party 7.02.01. Florence: Firenze University Press, 2013. http://dx.doi.org/10.36253/978-88-6655-353-3.

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The present Proceedings comprise the contributions that were presented at the 13th International Conference of the IUFRO W. Party 7.02.01 “Root and Butt Rot of Forest Trees” that was held in Italy from the 4th to the 10th of September 2011. The Conference started in Firenze than moved to FEM Research Centre, S. Michele all’Adige, Trento and continued in San Martino di Castrozza, Dolomite region. Root and Butt Rot of Forest Trees have a high biological and economic impact in forestry. The Proceedings were organized under seven headings: Genomics and Plant-Pathogen Interactions; Systematics, Taxonomy and Phylogeography; Ecology; Population Genetics; Etiology and Epidemiology; Disease Management and Control; New Reports, Diagnostics and Research on the Application of new Diagnostic Methods.

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26

Allendorf, Fred W., W. Chris Funk, Sally N. Aitken, Margaret Byrne, Gordon Luikart, and Agostinho Antunes. Conservation and the Genomics of Populations. 3rd ed. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780198856566.001.0001.

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Loss of biodiversity is among the greatest problems facing the world today. Conservation and the Genomics of Populations gives a comprehensive overview of the essential background, concepts, and tools needed to understand how genetic information can be used to conserve species threatened with extinction, and to manage species of ecological or commercial importance. New molecular techniques, statistical methods, and computer programs, genetic principles, and methods are becoming increasingly useful in the conservation of biological diversity. Using a balance of data and theory, coupled with basic and applied research examples, this book examines genetic and phenotypic variation in natural populations, the principles and mechanisms of evolutionary change, the interpretation of genetic data from natural populations, and how these can be applied to conservation. The book includes examples from plants, animals, and microbes in wild and captive populations. This third edition has been thoroughly revised to include advances in genomics and contains new chapters on population genomics, genetic monitoring, and conservation genetics in practice, as well as new sections on climate change, emerging diseases, metagenomics, and more. More than one-third of the references in this edition were published after the previous edition. Each of the 24 chapters and the Appendix end with a Guest Box written by an expert who provides an example of the principles presented in the chapter from their own work. This book is essential for advanced undergraduate and graduate students of conservation genetics, natural resource management, and conservation biology, as well as professional conservation biologists and policy-makers working for wildlife and habitat management agencies. Much of the book will also interest nonprofessionals who are curious about the role of genetics in conservation and management of wild and captive populations.

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27

Handbook of Statistical Genetics. 3rd ed. Wiley-Interscience, 2007.

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28

Foulkes, Andrea S. Applied Statistical Genetics with R. Springer, 2009.

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29

Guerra, Rudy. A Primer of Statistical Genetics. Chapman & Hall/CRC, 2009.

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30

Applied Statistical Genetics with R: For Population-Based Association Studies. Springer London, Limited, 2009.

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31

Genetic Data Analysis 2: Methods for Discrete Population Genetic Data. 2nd ed. Sinauer Associates, 1996.

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32

Gallais, A., C. Dillmann, and I. Goldringer. Quantitative Genetics and Breeding Methods: The Way Ahead (Les Colloques). Institute National de la Recherche Agronomique, 2001.

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33

(Editor), D. J. Balding, Chris Cannings (Editor), and Martin Bishop (Editor), eds. Handbook of Statistical Genetics. John Wiley & Sons, 2001.

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34

Stram, Daniel O. Design, Analysis, and Interpretation of Genome-Wide Association Scans. Springer, 2013.

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35

Kang, Manjit S. Handbook of Formulas and Software for Plant Geneticists and Breeders. Food Products Press, 2003.

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36

Kang, Manjit S. Handbook of Formulas and Software for Plant Geneticists and Breeders. Food Products Press, 2003.

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37

Xu, Shizhong. Principles of Statistical Genomics. Springer, 2014.

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38

Xu, Shizhong. Principles of Statistical Genomics. Springer London, Limited, 2012.

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39

Principles Of Statistical Genomics. Springer-Verlag New York Inc., 2008.

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40

Tavaré, Simon, and Ofer Zeitouni. Lectures on Probability Theory and Statistics: Ecole d'Eté de Probabilités de Saint-Flour XXXI - 2001 (Lecture Notes in Mathematics). Springer, 2004.

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41

(Editor), David J. Balding, Martin Bishop (Editor), and Chris Cannings (Editor), eds. Handbook of Statistical Genetics (2 Volume Set). Wiley, 2003.

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42

Stram, Daniel O. Design, Analysis, and Interpretation of Genome-Wide Association Scans. Springer, 2016.

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43

Stram, Daniel O. Design, Analysis, and Interpretation of Genome-Wide Association Scans. Springer, 2013.

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44

Stram, Daniel O. Design, Analysis, and Interpretation of Genome-Wide Association Scans. Springer London, Limited, 2013.

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45

Montgomery, Slatkin, and Veuille Michel, eds. Modern developments in theoretical population genetics: The legacy of Gustave Malécot. Oxford: Oxford University Press, 2002.

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46

(Editor), Montgomery Slatkin, and Michel Veuille (Editor), eds. Modern Developments in Theoretical Population Genetics: The Legacy of Gustave Malecot. Oxford University Press, USA, 2002.

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47

(Editor), Montgomery Slatkin, and Michel Veuille (Editor), eds. Modern Developments in Theoretical Population Genetics: The Legacy of Gustave Malecot. Oxford University Press, USA, 2002.

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48

Kjellsson, Gösta, Vibeke Simonsen, and Klaus Ammann. Methods for Risk Assessment of Transgenic Plants: II. Pollination, Gene-Transfer and Population Impacts. Birkhäuser, 2012.

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49

Láruson, Áki Jarl, and Floyd Allan Reed. Population Genetics with R. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198829539.001.0001.

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Population genetics is an inherently quantitative discipline. Because the focus of population genetics studies is usually on abstract concepts like the frequencies of genetic variants over time, it can at first glance be difficult to conceptualize and appropriately visualize. As more and more quantitative models and methods have become established in the discipline, it has become necessary for people just entering the field to quickly develop a good understanding of the many layers of complex approaches, so as to correctly interpret even basic results. An unfortunate side effect of the widespread implementation of ready-to-use quantitative software packages is that some facets of analysis can become rote, which at best might lead to implementation without the full understanding of the user and at worst, inappropriate application leading to misguided conclusions. In this book a “learning by doing” approach is employed to encourage readers to begin developing an intuitive understanding of population genetics concepts. The analytical software R, which has increasingly been the program of choice for early exposure to basic statistical programming, is freely available online, has cross-platform compatibility (Windows, Mac, and Linux all support distributions of R), and offers the potential for hands-on implementation by the students, in addition to using pre-packaged functions.

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50

Yan, Weikai, and Manjit S. Kang. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. Taylor & Francis Group, 2002.

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