Rui Borges

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Assignment 2

Inferring Bayesian trees

In this assignment, you will infer the Bayesian tree for your sequences.

  1. You will have to select one of the sequences in your multiple sequence alignment to serve as an outgroup for the Bayesian tree inference. Indicate and explain your choice.

  2. Set the model of evolution that you have obtained in the last task into MrBayes. Justify your options for the nst and rates. Remember that you obtain more information about the available models and rates by typig help lset on the MrBayes terminal. Run your MCMC by setting two runs and 100 000 generations. Use a sample frequency samplefreq that will allow you to sample 1000 generations, and to summarise the runs with sump and sumt, set a burnin that discards 20% of the initial samples. Justify your choices for the samplefreq and burnin.

  3. We now assess convergence. Analyze your MCMC .run1.p and .run2.p output files using Tracer. We will focus only on two parameters: the base composition of A and the exchangeability AC. According to their trace plots, are the two runs reaching a plateau, and are the two runs converging to the same regions? Complement your visual analyses of the trace plots with the ESS value: is it acceptable? Justify. According to your convergence analysis, do you think you need to run your MCMC for an additional number of generations, or the current samples are enough to summarize the posterior?

  4. We had discarded 20% of the samples when we summarized the model parameters. Based again on the trace plots of the base composition of A and the exchangeability AC, do you think that a 20% burn-in was an appropriate choice or too conservative/relaxed? Justify your answer.

  5. What is the posterior clade probability of the great ape’s clade? Is it well or poorly supported? Justify your answer by plotting the Bayesian tree with the respective support values. Indicate clearly which support values you are referring to.

Some notes: