ワ タ ナ ベ 研 究 チ ー ム @ NEW YORK TECH
» Join our lab: new NSF-funded postdoc position. Apply HERE.
» Meghan Forcellati wins Colbert Student Poster Prize at SVP!
» PI Watanabe is awarded the Cobb Award for Morphological Sciences by AAA.
For full list of codes: PI's GitHub page
PERDA: Polymorphic Entry Replacement Data Analysis
This TNT script helps assess the impact of poor intraspecific sampling on an existing data set by replacing each polymorphic state (e.g., ) with a single state (e.g., 0 or 1) and recording the conflicting tree topologies that result from this differential morph sampling. Running PERDA on data sets, even with poor intraspecific sampling (e.g., paleontological data), reveals clades, within which the taxonomy should be further investigated because character-based intraspecific variation is able to overcome interspecific variation. For further information, please refer to Watanabe 2016 Cladistics.
This Python program takes a NEWICK string file and a CSV file of a single continuous variable and conducts a permutational regression analysis on phenotypic and phylogenetic distances to create a histogram of the distribution of regression coefficients. NB: this program requires tree.py module to run, which can be downloaded through Peter Beerli's website. Written in Python v. 2.7.2.