Abstract
The package TransferEntropyPT provides R functions to calculate the transfer entropy (TE) [6] for time series of (binned) data. The package provides a function to assess the statistical significance of the TE using permutation tests on the sequential data of the time series. The underlying code base is written in C++ for computational efficiency and makes use of the boost and OpenMP libraries for parallelization of the data-parallel tasks in the permutation tests. In addition to p-values from hypothesis tests on independence, the package provides direct access to the percentiles themselves. An anticipatory toy model, as well as a biological network is used as show cases. Here, every time series concentrations of a single molecular species is tested and assessed against each other.
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Acknowledgments
The authors gratefully acknowledge (partial) financial support by the LOEWE projects iNAPO & compuGene of the Hessen State Ministry of Higher Education, Research and the Arts. The authors are grateful for the comments of anonymous referees that improved the manuscript and the style of presentation.
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Boba, P., Hamacher, K. (2017). TransferEntropyPT: An R Package to Assess Transfer Entropies via Permutation Tests. In: Feret, J., Koeppl, H. (eds) Computational Methods in Systems Biology. CMSB 2017. Lecture Notes in Computer Science(), vol 10545. Springer, Cham. https://doi.org/10.1007/978-3-319-67471-1_17
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DOI: https://doi.org/10.1007/978-3-319-67471-1_17
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