Bergmann Lab Resources


The Evolutionary Functional Morphology lab uses a variety of approaches and techniques. These include equipment and software for collecting data, code that we write in R to do analyses, and various statistical techniques. Below are a series of standard operating procedures (SOPs) that we use to standardize how we do things and ensure data consistency and quality (please obtain in-person training prior to doing these techniques), R code along with citations for analyses we have implemented, and Dr. Bergmann's Advanced Biostatistics (Biol 206/306) labs, covering more standard statistical techniques.

Lab Standard Operating Procedures


R code

DescriptionReference
Calculates a reduced major axis regression and its residuals in two ways, and calculates Kolmogorov-Smirnov and Shapiro-Wilks tests for normality on the residuals.
Bergman, P.J., Berk, C.P. 2012. The evolution of positive allometry of weaponry in horned lizards (Phrynosoma). Evolutionary Biology 39: 311-323.
Does a Mantel test to compare two matrices in different ways: You can compare just the lower triangle, the lower triangle and diagonal, or the whole matrix.
Bergmann, P.J., McElroy, E.J. 2014. Many-to-many mapping of phenotype to performance: An extension of the F-matrix for studying functional complexity. Evolutionary Biology 41: 546-560.
Uses multiple regression to construct an F-matrix and associated statistics and metrics, including the FFT and FTF matrices for a data set of multiple phenotypic traits and multiple performance measures.
Bergmann, P.J., McElroy, E.J. 2014. Many-to-many mapping of phenotype to performance: An extension of the F-matrix for studying functional complexity. Evolutionary Biology 41: 546-560.
Creates an F-array and associated statistics for multiple phenotypic traits, multiple performance measures, and multiple species related by a phylogeny. Uses the Mantel and F-matrix functions.
Bergmann, P.J., McElroy, E.J. 2014. Many-to-many mapping of phenotype to performance: An extension of the F-matrix for studying functional complexity. Evolutionary Biology 41: 546-560.
Does a randomization ANOVA of any design that can be handled by the aov function in R with a user-specified number of data randomizations.
Mitchell, A., Bergmann, P.J. 2016. Thermal and moisture habitat preferences do not maximize jumping performance in frogs. Functional Ecology 30: 733-742.


Advanced Biostatistics Labs (Biol 206/306, Fall 2016)


Callisaurus draconoides ready for video recording Dr. Bergmann using a racetrack Lizard X-ray

 

© 2005-2017 Philip J. Bergmann | Updated 1.26.2017