MORPHIX: Resolving sample identification bias in morphometrics analysis with a supervised machine learning package
Nima Mohseni,
Eran Elhaik
Abstract:Evolutionary biologists, primarily anatomists and ontogenists, employ modern geometric morphometrics to quantitatively analyse physical forms (e.g., skull morphology) and explore relationships, variations, and differences between samples and taxa using landmark coordinates. The standard approach comprises two steps, Generalised Procrustes Analysis (GPA) followed by Principal Component Analysis (PCA). PCA projects the superimposed data produced by GPA onto a set of uncorrelated variables, which can be visualise… Show more
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