ben stöver ws 2012/2013 ancestral state reconstruction molecular phylogenetics – exercise

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Ben Stöver WS 2012/2013 Ancestral state reconstruction Molecular Phylogenetics – exercise

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Page 1: Ben Stöver WS 2012/2013 Ancestral state reconstruction Molecular Phylogenetics – exercise

Ben Stöver WS 2012/2013

Ancestral state reconstruction

Molecular Phylogenetics – exercise

Page 2: Ben Stöver WS 2012/2013 Ancestral state reconstruction Molecular Phylogenetics – exercise

Ben Stöver

Ancestal state reconstruction with BayesTraits

Fortgeschrittenenmodul Molecular Phylogenetics

Winter term 2012/2013

13.02.2012

1 Ancestral state reconstruction1. Ancestral state reconstruction 2

• Reconstructing character states of acenstral nodes

• Tree topology is given• Terminal character states are given

• Top left charts: Female gametangia (green: ventral, red: marginal, blue: central)

• Top right charts: Mycothallus (green: parenchymal, red: epidermal, blue: none)

• Bottom charts: Scales (yellow: small, green: broad marginal, red: lateral on margin, blue: broad central)

Page 3: Ben Stöver WS 2012/2013 Ancestral state reconstruction Molecular Phylogenetics – exercise

Ben Stöver

Ancestal state reconstruction with BayesTraits

Fortgeschrittenenmodul Molecular Phylogenetics

Winter term 2012/2013

13.02.2012

2 Mesquite2. Mesquite 3

• Modular software system• Ancestral state reconstruction

with parsimony or likelihood• (No Bayesian methods

available)• Many other features• Distributed under GPL

Page 4: Ben Stöver WS 2012/2013 Ancestral state reconstruction Molecular Phylogenetics – exercise

Ben Stöver

Ancestal state reconstruction with BayesTraits

Fortgeschrittenenmodul Molecular Phylogenetics

Winter term 2012/2013

13.02.2012

3.1 BayesTraits – overview3. BayesTraits 4

Parts of the software:

• BayesMultistate• Reconstructs characters with multiple (more than two) states

• BayesDiscrete• Analyze correlated evolution between pairs of discrete binary traits

• BayesContinues• Analysis of the evolution of continuously varying traits (e.g. length of an

organ)

• BayesTraits is a command line based software (like PAUP* and MrBayes)

• Performs maximum likelihood or Bayesian reconstruction.

Page 5: Ben Stöver WS 2012/2013 Ancestral state reconstruction Molecular Phylogenetics – exercise

Ben Stöver

Ancestal state reconstruction with BayesTraits

Fortgeschrittenenmodul Molecular Phylogenetics

Winter term 2012/2013

13.02.2012

3.2 Starting BayesTraits

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• BayesTraits takes two command line parameters.• BayesTraits.exe <TreeFile> <DataFile>

• The tree file may also contain a tree distribution (e.g. from MrBayes)• The data file contains a table specifying the terminal character states.

• In the start menu the part of the program to be used must be selected

• The method is selectes afterwards

3. BayesTraits

Page 6: Ben Stöver WS 2012/2013 Ancestral state reconstruction Molecular Phylogenetics – exercise

Ben Stöver

Ancestal state reconstruction with BayesTraits

Fortgeschrittenenmodul Molecular Phylogenetics

Winter term 2012/2013

13.02.2012

3.3 BayesTraits commands

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• sample <n>: Sets the sample frequency.• iterations <n>: Specifies the number of generations for the MCMC-

algorithm.• burnin <n>: Sets the generation count of the burin.• revjumphp: Specifies the distribution of prior probabilities (only

for MCMC)• AddNode: Defines an exact node to be reconstructed.

(e.g.: AddNode Node01 51 52 50 49 47 48)• AddMRCA: Defines a node to be reconstructed that is the

most recent common ancestor of the specified taxa (but might also be the acestor of additional taxa.)

• fossil: Specifies an ancestral state already known. (e.g.: fossil Node1 0 51 52 50 49 47 48 sets

the state of Node1=0)• info: Prints out information of the current settings.• run: Starts the analysis.

3. BayesTraits

Page 7: Ben Stöver WS 2012/2013 Ancestral state reconstruction Molecular Phylogenetics – exercise

Ben Stöver

Ancestal state reconstruction with BayesTraits

Fortgeschrittenenmodul Molecular Phylogenetics

Winter term 2012/2013

13.02.2012

3.4 Output of BayesTraits

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• BayesTraits generates a text file containing a table with the posterior probabilities of the samples (or likelihoods).

• Each line describes one sample the MCMC algorithm took. • (For ML with a single tree, there will only be one line.)• There is one column for each state of each character that was

reconstructed.

3. BayesTraits