Phylogenetic inference from atomised 3D morphometric data: a case study using kangaroos

Reconstructing phylogeny from morphological data remains mired in investigator biases, including subjective inclusion and discretisation of phenotypic variation. Geometric morphometrics and multivariate statistical analyses provide an alternative array of tools for studying variation in morphological traits. However, direct analysis of landmark data is often unreliable for phylogeny reconstruction. Morphological variation is typically highly correlated among nearby landmarks and may evolve saltationally between adaptive peaks instead of gradually, thereby violating the assumptions of typical continuous models. To address these concerns, we developed an approach to more objectively discretise morphometric data and applied it to 3D surface scans of mandibles and postcranial elements of Macropodiformes (kangaroos, bettongs, and rat-kangaroos). These scans were partitioned into sets of locally co-varying landmarks which approximate functional units. These “atomised” characters were then dis..., , , # Data from: Phylogenetic inference from atomised 3D morphometric data: a case study using kangaroos

[https://doi.org/10.5061/dryad.rn8pk0pm4](https://doi.org/10.5061/dryad.rn8pk0pm4)

## Description of the data and file structure

Supplementary materials providing landmark definitions, raw landmark and mean rotated landmark coordinates, phylogenetic character matrices (available in data.zip), R code for analyses. See main paper and supplementary information for more details.

### Files in data.zip:

#### **Character matrices:** 

phylogenetic character matrices for analysis in PAUP*, IQ-TREE, TNT and ContML. 

Matrices are coded as multistate or binary characters resulting from discretization using clustering approaches, a branch length criterion, or tree sampling (supertree) approach described in the main manuscript and supplementary information.

#### **Landmark definitions:**

landmark_definition_all.xlsx

Landmark definition for each subregion with corresponding sliding semilandma...,