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GeometricMorphometricsMix

Miscellaneous geometric morphometric functions

This package provides a diverse set of functions for geometric morphometric analyses, including shape integration, disparity, association, and more. It is designed for researchers, students, and practitioners in geometric morphometrics.

Originally developed as a resource for students in the Geometric Morphometrics course (Physalia Courses), these functions have been complemented over the years with many new functions, and are now distributed as an R package for broader accessibility and ease of use.

Installation

From Github, using devtools

library(devtools)
install_github("fruciano/GeometricMorphometricsMix", build_vignettes=TRUE)

Citation

Currently, there is no formal publication describing the package (but this may be available in the future). Please, use citation() to identify the most appropriate current citation of GeometricMorphometricsMix. Importantly, each function provides reasonable comments and references to the methods, which can (and should) be used when using the functions in the package (in addition to the usual citation to the package itself).

Documentation and Help

Each function in the package is documented with usage examples and references.

Currently available functions

adjRand_test : Permutation test of the adjusted Rand index, which quantifies the agreement between two partitions (e.g., classification of specimens obtained using different methods)
BTailTest : Comparison of disparity between two groups
critical_angle : Critical angle for the test of difference between two vectors
disparity_resample : Obtain resampling estimates (bootstrap or rarefaction) of disparity statistics
disparity_test : Comparison of disparity between two groups
dist_mean_boot : Bootstrap estimates of the distance between group means
EscoufierRV : Computation of Escoufier RV, which quantifies levels of association between blocks of variables (Escoufier 1973 - Biometrics)
Kmultparallel : Parallelised computation of Adams’ Kmult (useful for distributions of trees, see Fruciano et al. 2017 - Ecology and Evolution)
LM_relativepos_check : Check relative position of landmarks, comparing it to a reference specimen (useful to identify switched landmarks and similar in raw data)
parallel_analysis : Perform parallel analysis (useful to choose a number of principal components for dimensionality reduction)
pls : Perform partial least squares (PLS) analysis
pls_major_axis : For a partial least squares (PLS) analysis, compute the major axis of PLS scores, project data onto the axis and compute predicted shapes for the major axis scores thus obtained.
ProjectOrthogonal : Projects data to subspace orthogonal to a given vector (for use in allometric correction, see Burnaby 1966 - Biometrics; Rohlf & Bookstein 1987 - Systematic Zoology; for use in dealing with measurement error, see Valentin et al. 2008 - Journal of Fish Biology; Fruciano 2016 - Development Genes and Evolution)
rescale_by_landmark_distance : Convenience function to rescale configurations of landmarks based on a vector of inter-landmark distances
reversePCA : Simple function to obtain the original variables (e.g., shape) from PC scores (and mean)
rotate_landmarks: Apply a user-defined rotation of a landmark configuration about the origin
rarefied_convex_hull : Computation of rarefied estimates of n-dimensional convex hull volume (a measure of disparity/morphospace occupation) - deprecated
rarefied_disparity : Rarefied estimates of some measures of disparity/morphospace occupation - deprecated
repeated_measures_test : Test of difference between two repeated measures
RVrarefied : Computation of rarefied estimates of Escoufier RV (see Fruciano et al. 2013 - Plos One)
RVcomparison : Permutation test for the difference in Escoufier RV (see Fruciano et al. 2013 - Plos One)
scaled_variance_of_eigenvalues : Compute estimates of the scaled variance of eigenvalues (a commonly used measure of integration)
TestOfAngle : Test of angle between two vectors, optionally allowing “flipping” of one of the two

Function Groups by Analysis Type

Analysis Type	Functions	Description
Analysis of Disparity	`BTailTest`	Traditional comparison of disparity between two groups
	`disparity_resample`	Resampling estimates of disparity
	`disparity_test`	Comparison of disparity between two groups
	`rarefied_convex_hull`	Computation of rarefied estimates of n-dimensional convex hull volume (measure of disparity/morphospace occupation) - deprecated
	`rarefied_disparity`	Rarefied estimates of various measures of disparity/morphospace occupation - deprecated
Integration/Association/Modularity	`EscoufierRV`	Computation of Escoufier RV coefficient, quantifying association between blocks of variables
	`RVrarefied`	Computation of rarefied estimates of Escoufier RV to account for sample size
	`RVcomparison`	Permutation test for the difference in Escoufier RV between datasets
	`scaled_variance_of_eigenvalues`	Compute estimates of the scaled variance of eigenvalues (measure of integration)
	`pls`	Perform partial least squares (PLS) analysis for covariation between blocks
	`pls_major_axis`	Compute major axis of PLS scores and predicted shapes along this axis
Vector/Angle Analysis	`critical_angle`	Critical angle for the test of difference between two vectors
	`TestOfAngle`	Test of angle between two vectors, with optional “flipping” of one vector
Group Comparison and Classification	`adjRand_test`	Permutation test of the adjusted Rand index, quantifying agreement between two partitions
	`dist_mean_boot`	Bootstrap estimates of the distance between group means
	`repeated_measures_test`	Test of difference between two repeated measures
Data Transformation and Manipulation	`ProjectOrthogonal`	Projects data to subspace orthogonal to a given vector (for allometric correction)
	`rescale_by_landmark_distance`	Rescale configurations of landmarks based on inter-landmark distances
	`reversePCA`	Obtain original variables from PC scores and mean
	`rotate_landmarks`	Apply a user-defined rotation of a landmark configuration
Phylogenetic Comparative Analysis	`Kmultparallel`	Parallelised computation of Adams’ Kmult (for distributions of trees)
Quality Control and Diagnostics	`LM_relativepos_check`	Check relative position of landmarks against a reference specimen
Dimensionality Reduction	`parallel_analysis`	Perform parallel analysis to determine number of principal components to retain

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.