mattbk / momocs

Morphometrics using R

News

• Momocs version 1.0 "Mataa" 🗿 will be released on CRAN in March 2016
• Momocs' online documentation lives there

Momocs, morphometrics using R

Momocs:

• is a complete toolkit for morphometrics, from data extraction to multivariate analyses.
• includes most common 2D morphometrics approaches : outlines, open outlines, configurations of landmarks, traditional morphometrics, and facilities for data preparation, manipulation and visualization with a consistent grammar throughout.
• allows reproducible, complex morphometric analyses, paves the way for a pure open-source workflow in R, and other morphometrics approaches should be easy to plug in, or develop from, on top of this canvas.
• hinges on the core functions developed in the must-have book Morphometrics with R by Julien Claude (2008).

Use it

CRAN version

install.packages("Momocs")

Last version

That's always a good idea to use the last version.
Be sure to have devtools installed (install.packages("devtools")), then:

devtools::install_github("vbonhomme/Momocs", build_vignettes= TRUE)

How to cite it

citation("Momocs")

You are welcome to

• propose ideas and report bugs
• offer your published data to the world
• ask for hotline and/or collaborate and/or hire me: [email protected]

Features

(* = on its way)

Data acquisition + Babel

• Outline extraction
• Landmark definition on outlines (via StereoMorph)
• Open curves digitization with bezier curves (via StereoMorph)
• Import/Export from/to .nts, .tps, PAST, .txt, etc.*

Outline analysis

• Elliptical Fourier analysis
• Radius Variation Fourier analysis
• Tangent Angle Fourier analysis
• Calibration for all methods

Open-outlines

• Natural (raw) polynomials (npoly)
• Orthogonal (Legendre) polynomials (opoly)
• Discrete Cosinus Transform (dfourier)
• Calibration for all methods
• bezier core functions

Configuration of landmarks

• Full Generalized Procrustes Adjustment (fgProcrustes)
• Resistant Fit Procrustes Adjustments*
• Sliding semi-landmarks

Traditional morphometrics and global shape descriptors

• Facilities for multivariate analysis (see flowers)
• A long list of shape scalars (eg. coo_eccentricity, coo_rectilinearity, etc.)

Data handling

• filter, select, slice, mutate and other verbs ala dplyr
• New verbs useful for morphometrics such as combine and chop, to handle several 2D views
• Permutation methods to resample data (perm, breed)

Multivariate analysis

• Mean shape (groupwise) calculations (mshapes)
• Principal component analysis (PCA)
• Multivariate analysis of variance (MANOVA + pairwise testing MANOVA_PW)
• Linear discriminant analysis and screening (LDA)
• Hierarchical clustering (CLUST)
• K-means (KMEANS)

Graphical methods

• Family pictures and quick inspection of whole datasets
• Some ggplot2 plots, when useful
• Morphological spaces for PCA
• Thin plate splines and variation around deformation grids

Various

• Datasets for all types of data (bot, trilo, mosquito, hearts, olea, shapes, wings, oak, molars, flower, chaff, charring)
• Vignettes (browseVignettes("Momocs"))
• Shiny demonstrators/helpers. See Momecs
• Online documentation

Architecture

Here is a scheme of the Momocs' architecture: