Introduction
1.
Background
1.1.
Practice
1.2.
Prerequisites
1.3.
Resources
2.
Retrieving sequences
2.1.
Theory
2.2.
Practice
2.2.1.
Retrieving sequences example
2.2.2.
Retrieving annotations example
2.2.3.
Exercises
3.
Sequence alignment
3.1.
Theory
3.2.
Practice
3.2.1.
Nucleotide alignment
3.2.2.
Reverse alignment
3.2.3.
Exercise
4.
Distance-based analyses
4.1.
Theory
4.2.
Practice
4.2.1.
Neighbour joining example
4.2.2.
Exercise
5.
Recombination
5.1.
Theory
5.2.
Practice
5.2.1.
Exercise
6.
Maximum likelihood based analyses
6.1.
Theory
6.2.
Practice
6.2.1.
Model choice example
6.2.2.
RAxML example
6.2.3.
Tree reconstruction exercise
7.
Visualising trees
7.1.
Practice
7.1.1.
Exercise
8.
Time-stamped phylogenies
8.1.
Theory
8.2.
Practice
8.2.1.
Fixing the maximum likelihood tree
8.2.2.
Time tree exercise
9.
Bayesian reconstruction of time trees
9.1.
Theory
9.2.
Practice
9.2.1.
MrBayes example
10.
Effective population size estimation
10.1.
Theory
10.2.
Practice
10.2.1.
Fitting skyline
10.2.2.
Exercise
11.
Structured populations
11.1.
Theory
11.2.
Practice
11.2.1.
'Mugration' exercise
12.
References
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Getting timetrees
We will use MrBayes to generate time trees
R is useful to generate the constraints on sampling times