Provides functions to calculate the normalised Lineage-Through-Time (nLTT) statistic, given two phylogenetic trees. The nLTT statistic measures the difference between two Lineage-Through-Time curves, where each curve is normalised both in time and in number of lineages.

c(person("Thijs","Janzen", email = "thijsjanzen@gmail.com",role=c("aut","cre")),
person("Richel","Bilderbeek",email="richel@richelbilderbeek.nl", role=c("aut")))
Provides functions to calculate the normalised Lineage-Through-
Time (nLTT) statistic, given two phylogenetic trees. The nLTT statistic measures
the difference between two Lineage-Through-Time curves, where each curve is
normalised both in time and in number of lineages.
DDD, ggplot2, Hmisc, knitr, microbenchmark, plyr, reshape2,
rmarkdown, TESS, testit, testthat, TreeSim
Thijs Janzen [aut, cre],
Richel Bilderbeek [aut]

DDD, ggplot2, Hmisc, knitr, microbenchmark, plyr, reshape2,
rmarkdown, TESS, testthat, TreeSim

c(person("Thijs","Janzen", email = "thijsjanzen@gmail.com",role=c("aut","cre")),
person("Richèl J.C.", "Bilderbeek", email = "richel@richelbilderbeek.nl", role = c("aut"), comment = c(ORCID = "0000-0003-1107-7049")),
person("Pedro", "Neves", email = "p.m.santos.neves@rug.nl", role = "ctb"))
DDD, ggplot2, Hmisc, knitr, lintr, microbenchmark, plyr,
reshape2, rmarkdown, TESS, testthat (>= 2.1.0), TreeSim, DAISIE
Thijs Janzen [aut, cre],
Richèl J.C. Bilderbeek [aut] (<https://orcid.org/0000-0003-1107-7049>),
Pedro Neves [ctb]

TreeSim, DDD, ggplot2, Hmisc, knitr, lintr, microbenchmark,
plyr, reshape2, rmarkdown, TESS, testthat, DAISIE

Create n-Dimensional, Quasi-Proportional Venn Diagrams
person("Victor", "Quesada", email = "quesadavictor@uniovi.es", role=c("aut", "cre", "cph"))
Provides an interface for the nVenn algorithm
(Perez-Silva et al. 2018) <DOI:10.1093/bioinformatics/bty109>. This algorithm works for any number of sets,
and usually yields
pleasing and informative Venn diagrams with proportionality information.
However, representing more than six sets takes a long time and is hard to interpret, unless many of the
regions are empty. If you cannot make sense of the result, you may want to consider 'UpSetR'
<https://cran.r-project.org/package=UpSetR/README.html>.