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E-grāmata: Analysis of Phylogenetics and Evolution with R

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  • Formāts: PDF+DRM
  • Sērija : Use R!
  • Izdošanas datums: 25-Nov-2006
  • Izdevniecība: Springer-Verlag New York Inc.
  • Valoda: eng
  • ISBN-13: 9780387351001
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  • Formāts: PDF+DRM
  • Sērija : Use R!
  • Izdošanas datums: 25-Nov-2006
  • Izdevniecība: Springer-Verlag New York Inc.
  • Valoda: eng
  • ISBN-13: 9780387351001
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This book integrates a variety of data analysis methods into a single and flexible interface: the R language. Since R is a powerful and complete environment for statistics and visual display, researchers can customize the outputs to fit their requirements.

This book integrates a wide variety of data analysis methods into a single and flexible interface: the R language. The book starts with a presentation of different R packages and gives a short introduction to R for phylogeneticists unfamiliar with this language. The basic phylogenetic topics are covered. The chapter on tree drawing uses R's powerful graphical environment. A section deals with the analysis of diversification with phylogenies, one of the author's favorite research topics. The last chapter is devoted to the development of phylogenetic methods with R and interfaces with other languages (C and C++). Some exercises conclude these chapters.

Recenzijas

From the reviews: "This book is a rich source of information. The general introduction in R makes it easy, also for R beginners, to understand the structure of data in R ! . explains all the possibilities the ape package offers, starting from loading data (trees, alignments), handling them, to statistics and the plotting of trees step by step by giving many additional information about the basics in R. ! it is a very useful manual giving many examples that facilitate the immediate application of the presented functions." (Natalie Cusimano, www.eeslmu.de, July, 2007) "'Analysis of Phylogenetics and Evolution with R', published in 2006 in Springer, seems very thin at a first glance but very soon proved to be highly useful for me. ! information is well chosen and considers (nearly) all the functions necessary to carry out the analyses presented in this book. Readers who are completely new to R will find these ! especially usefull. ! The book constitutes a well-written documentation and facilitates the use of R as an integrative computational environment for phylogenetics and evolution." (Christoph Heibl, www.eeslmu.de, July, 2007) "The book by Paradis ! is filled with examples and case studies illustrating how to use features of the existing packages. It is the sort of book where you sit in front of your computer and read a bit, tinker a bit, read a bit more, and gradually increase your confidence with the R environment. ! I think people will find Analysis of Phylogenetics and Evolution with R to be a very useful reference book. ! So ! buy the book, and get involved!" (Barbara R. Holland, Systematic Biology, Vol. 56 (4), 2007) "Paradis succeeds in teaching how one can harness a substantial portion of these analyses through R and ape package. The key to Paradis's success lies in his book's numberous examples and their relevance to real problems phylogenetecists face...This book is ideal for graduate-level course for evolutionary biologists who want to learn how to construct their own statisticsal analyses, as well as statisticians looking for practical experience...I plan to adopt [ this book] for a hands-on course on solving real phlogenetics problems." (Marc A Suchard, Biometrics, December 2007) "Analysis of phylogenetics and Evolution With R is, in effect, a user's manual for several R packages ! . The book explains various statistical analysis of interest to evolutionary biologists in R using these packages. ! I can also envision this as an excellent textbook. ! can help organize the ideas, and make it easier for students to implement them on data. ! This will make the foreign elements of the class (biology for statisticians, statistics for biologists) more concrete and easier to learn." (M. Last, Journal of the American Statistical Association, Vol. 102 (480), 2007) "This book is a handbook for a program package for doing phylogenetic and evolutionary analysis on the open-source computational statistics platform R. ! The intended audience is researchers in evolutionary biology and population genetics, and in bioinformatics, where R has already become a widely used statistical environment. ! A good selection of specific computational exercises are provided, based on publicly available data sets." (Daniel M. Burns, Mathematical Reviews, Issue 2008 h)

Introduction
1(8)
Strategic Considerations
1(3)
Notations
4(1)
Preparing the Computer
5(4)
Installations
5(2)
Configurations
7(2)
First Steps in R for Phylogeneticists
9(16)
The Command Line Interface
9(2)
The Data Structures
11(7)
Vector
11(3)
Factor
14(1)
Matrix
15(1)
Data Frame
16(1)
List
17(1)
The Help System
18(1)
Creating Graphics
19(1)
Saving and Restoring R Data
20(1)
Using R Functions
20(1)
Repeating Commands
21(2)
Loops
21(1)
Apply-Like Functions
22(1)
Exercises
23(2)
Phylogenetic Data in R
25(40)
Phylogenetic Data as R Objects
25(3)
The Class ``phylo'' (ape)
26(1)
The Class ``phylog'' (ade4)
27(1)
The Class ``matching'' (ape)
27(1)
The Class ``treeshape'' (apTreeshape)
28(1)
Reading Phylogenetic Data
28(5)
Phylogenies
28(2)
Reading Internet Tree Databases
30(1)
Molecular Sequences
30(3)
Writing Data
33(2)
Manipulating Data
35(9)
Basic Tree Manipulation
35(1)
Rooted Versus Unrooted Trees
36(1)
Dichotomous Versus Multichotomous Trees
37(1)
Summarizing and Comparing Trees
38(1)
Converting Objects
39(1)
Manipulating DNA Data
40(4)
Generating Random Trees
44(2)
Case Studies
46(18)
Sylvia Warblers
46(4)
Phylogeny of the Felidae
50(2)
Snake Venom Proteome
52(3)
Mammalian Mitochondrial Genomes
55(7)
Butterfly DNA Barcodes
62(2)
Exercises
64(1)
Plotting Phylogenies
65(30)
Simple Tree Drawing
65(18)
Annotating Trees
71(9)
Showing Clades
80(3)
Combining Plots
83(6)
Large Phylogenies
89(3)
Perspectives
92(2)
Exercises
94(1)
Phylogeny Estimation
95(38)
Distance Methods
96(4)
Calculating Distances
96(3)
Simple Clustering and UPGMA
99(1)
Neighbor-Joining
100(1)
Maximum Likelihood Methods
100(12)
Substitution Models: A Primer
101(5)
Estimation with Molecular Sequences
106(4)
Finding the Maximum Likelihood Tree
110(1)
DNA Mining with PHYML
111(1)
Bootstrap Methods and Distances Between Trees
112(7)
Resampling Phylogenetic Data
113(2)
Bipartitions and Computing Bootstrap Values
115(3)
Distances Between Trees
118(1)
Consensus Trees
118(1)
Molecular Dating
119(2)
Case Studies
121(10)
Sylvia Warblers
121(4)
Phylogeny of the Felidae
125(4)
Butterfly DNA Barcodes
129(2)
Perspectives
131(1)
Exercises
131(2)
Analysis of Macroevolution with Phylogenies
133(50)
Phylogenetic Comparative Methods
133(21)
Phylogenetically Independent Contrasts
135(3)
Phylogenetic Autoregression
138(1)
Autocorrelative Models
139(3)
Multivariate Decomposition
142(2)
Generalized Least Squares
144(3)
Generalized Estimating Equations
147(2)
Mixed Models and Variance Partitioning
149(2)
The Ornstein--Uhlenbeck Model
151(2)
Perspectives
153(1)
Estimating Ancestral Characters
154(6)
Continuous Characters
155(1)
Discrete Characters
156(4)
Analysis of Diversification
160(12)
Graphical Methods
161(2)
Birth--Death Models
163(4)
Survival Models
167(2)
Goodness-of-Fit Tests
169(1)
Tree Shape and Indices of Diversification
170(2)
Perspectives
172(1)
Case Studies
173(7)
Sylvia Warblers
173(3)
Phylogeny of the Felidae
176(4)
Exercises
180(3)
Developing and Implementing Phylogenetic Methods in R
183(16)
Features of R
183(4)
Object-Orientation
183(2)
Variable Definition and Scope
185(1)
How R Works
186(1)
Writing Functions in R
187(2)
Interfacing R with Other Languages
189(3)
Simple Interfaces
189(1)
Complex Interfaces
190(2)
Writing R Packages
192(1)
A Minimalist Package
192(1)
The Documentation System
193(1)
Performance Issues and Strategies
193(6)
References 199(10)
Index 209