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Müller  Nicola
Müller Nicola committed Jun 18, 2018
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Phylogeographic methods can help reveal the movement of genes between populations of organisms. This has been widely used to quantify pathogen movement between different host populations, the migration history of humans, and the geographic spread of languages or the gene flow between species using the location or state of samples alongside sequence data. Phylogenies therefore offer insights into migration processes not available from classic epidemiological or occurrence data alone.

The structured coalescent allows to coherently model the migration and coalescent process, but struggles with complex datasets due to the need to infer ancestral migration histories. Thus, approximations to the structured coalescent, which integrate over all ancestral migration histories, have been developed. This tutorial gives an introduction into how a MASCOT analysis in BEAST2 can be set-up. MASCOT is short for **M**arginal **A**pproximation of the **S**tructured **CO**alescen **T** and implements a structured coalescent approximation {% cite Mueller2017 --file Mascot-Tutorial/master-refs %}. This approximation doesn't require migration histories to be sampled using MCMC and therefore allows to analyse phylogenies with more than three or four states.
The structured coalescent allows to coherently model the migration and coalescent process, but struggles with complex datasets due to the need to infer ancestral migration histories. Thus, approximations to the structured coalescent, which integrate over all ancestral migration histories, have been developed. This tutorial gives an introduction into how a MASCOT analysis in BEAST2 can be set-up. MASCOT is short for **M**arginal **A**pproximation of the **S**tructured **CO**alescen **T** {% cite mueller2017mascot --file Mascot-Tutorial/master-refs %} and implements a structured coalescent approximation {% cite Mueller2017 --file Mascot-Tutorial/master-refs %}. This approximation doesn't require migration histories to be sampled using MCMC and therefore allows to analyse phylogenies with more than three or four states.

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# Practical: Parameter and State inference using the approximate structured coalescent

In this tutorial we will estimate migration rates, effective population sizes and locations of internal nodes using the marginal approximation of the structured coalescent implemented in BEAST2, MASCOT.
In this tutorial we will estimate migration rates, effective population sizes and locations of internal nodes using the marginal approximation of the structured coalescent implemented in BEAST2, MASCOT {% cite mueller2017mascot --file Mascot-Tutorial/master-refs %}.

The aim is to:

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# Useful Links

If you interested in the derivations of the marginal approximation of the structured coalescent, you can find them here {% cite Mueller2017 --file Mascot-Tutorial/master-refs %}. This paper also explains the mathematical differences to other methods such as the theory underlying BASTA. To get a better idea of how the states of internal nodes are calculated, have a look in this paper {% cite mueller2017mascot --file Mascot-Tutorial/master-refs %}.

- MASCOT source code: [https://github.com/nicfel/Mascot](https://github.com/nicfel/Mascot)
- [Bayesian Evolutionary Analysis with BEAST 2](http://www.beast2.org/book.html) {% cite BEAST2book2014 --file Mascot-Tutorial/master-refs.bib %}
- BEAST 2 website and documentation: [http://www.beast2.org/](http://www.beast2.org/)
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