"Introduction to phylogenetic analysis with R"
Delivered by Dr. Emmanuel Paradis
http://prstatistics.com/course/introduction-to-phylogenetic-analysis-with-r-phyg/
This course will run from 31st October – 4th November, Millport Field Station, Ilse of Cumbrae, Scotland
The main objectives of the course are to teach the theoretical bases of phylogenetic analysis, and to give the ability to initiate a phylogenetic analysis starting from the files of molecular sequences until the interpretation of the results and the graphics. The introduction will cover a brief historical background and an overview of the different methods of phylogenetic inference. Different kinds of data will be considered, but with a special emphasis on DNA sequences. The software used will be based on R and several specialized packages (particularly ape and phangorn). Other software will be used (e.g., MUSCLE or Clustal) called from R. Overall, the course will cover almost all aspects of phylogenetic inference from reading/downloading the data to plotting the results. This course is intended for PhD and postgraduate students, researchers and engineers in evolutionary biology, systematics, population genetics, ecology, conservation.
Course content is as follows
Day 1
• Refresher on R: data structures, data manipulation with the indexing system, scripts, using the help system.
• Introduction to phylogenetic inference.
• Basics on phylogenetic data (sequences, alignments, trees, networks, “splits”) and other data in R.
• Reading / writing data from files or from internet.
• Matching data. Manipulating labels. Subsetting data.
• Main package: ape.
Day 2
• Plotting and annotating trees.
• Theory of sequence alignment. Comparing alignments. Graphical analyses of alignments.
• Main packages: ape (with MUSCLE and Clustal).
Day 3
• Theory and methods of phylogeny reconstruction.
• Parsimony methods.
• Evolutionary distances.
• Distance-based methods: General principles and the main methods (NJ, BIONJ, FastME, MVR).
• Methods for incomplete distances matrices (NJ*, BIONJ*, MVR*). Methods for combining several matrices (SDM).
• Main packages: ape, phangorn.
Day 4
• Theory of maximum likelihood estimation.
• Application to phylogeny reconstruction.
• Substitution models.
• Tree space and topology estimation.
• Main packages: ape, phangorn.
Day 5
• Tree comparison, consensus methods.
• Topological space and distances.
• Bootstrap.
• Bayesian methods.
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Upcoming courses - email for details [log in to unmask]
1. ADVANCES IN SPATIAL ANALYSIS OF MULTIVARIATE ECOLOGICAL DATA (July)
2. INTRODUCTION TO BIOINFORMATICS USING LINUX (August)
3. GENETIC DATA ANALYSIS / EXPLORATION USING R (August)
4. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (August)
5. INTRODUCTION TO PYTHON FOR BIOLOGISTS (October)
6. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (October)
7. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (October)
8. SPATIAL ANALYSIS OF ECOLOGIC AL DATA USING R (November)
9. ADVANCING IN STATISTICAL MODELLING USING R (December)
10. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (January)
11. ADVACNED PYTHON FOR BIOLOGISTS (February)
12. NETWORK ANALYSIS FOR ECOLOGISTS (March)
13. INTRODUCTION TO GEOMETRIC MORPHOMETRICS USING R (June)
Dates still to be confirmed - email for details [log in to unmask]
• STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
• INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS
• BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS
Oliver Hooker
PR Statistics
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