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README.md

nLTT

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Repository for the R nLTT package

Installing this package

Make sure you have the package devtools installed.

Then, from within R do, for the stable version:

devtools::install_github("richelbilderbeek/nLTT")

For the bleeding-edge version:

devtools::install_github("richelbilderbeek/nLTT", ref = "develop")

What is the nLTT statistic?

The nLTT statistic is a likelihood free summary statistic to compare the similarity between two phylogenetic trees. It calculates the distance between the lineage through time curves of the two trees, after normalizing the lineage through time curves with respect to the maximum number of lineages obtained in each tree, and with respect to the total time between the root and the tips of the tree (see also the wiki).

A more detailed description, and a detailed analysis of the performance of the nLTT statistic can be found in the following paper:

Janzen, Thijs, Sebastian Höhna, and Rampal S. Etienne. "Approximate Bayesian computation of diversification rates from molecular phylogenies: introducing a new efficient summary statistic, the nLTT." Methods in Ecology and Evolution 6.5 (2015): 566-575. link

What else does the package do?

Apart from providing functions that calculate the nLTT statistic, the nLTT package for R also provides functions to:

  • plot the normalized Lineages-Through-Time plot for a single, or for multiple, trees
  • calculate and plot the average Lineages-Through-Time plot for multiple trees
  • estimate the parameters of a model for which the likelihood is known (for comparison), using MCMC (as used in the paper)
  • estimate the parameters of a model for which no likelihood is available, using ABC-SMC (as used in the paper)

Papers using the nLTT statistic

Janzen, Thijs, and Rampal Etienne. "Inferring the role of habitat dynamics in driving diversification: evidence for a species pump in Lake Tanganyika cichlids." bioRxiv (2017): 085431. link

Ibeh, Neke, and Stephane Aris-Brosou. "Estimation of sub-epidemic dynamics by means of Sequential Monte Carlo Approximate Bayesian Computation: an application to the Swiss HIV Cohort Study. bioRxiv (2016): 085993. link

Giardina F, Romero-Severson EO, Albert J, Britton T, Leitner T (2017) Inference of Transmission Network Structure from HIV Phylogenetic Trees. PLOS Computational Biology 13(1): e1005316. link

McCloskey, Rosemary M., Richard H. Liang, and Art FY Poon. "Reconstructing contact network parameters from viral phylogenies." Virus evolution 2.2 (2016): vew029. link

Janzen, Thijs, Sebastian Höhna, and Rampal S. Etienne. "Approximate Bayesian computation of diversification rates from molecular phylogenies: introducing a new efficient summary statistic, the nLTT." Methods in Ecology and Evolution 6.5 (2015): 566-575. link

Acknowledgements

  • @franciscorichter: bug reporting

I want to contribute!

See CONTRIBUTING.md

Code of Conduct

See code_of_conduct.md