DOI: 10.5061/dryad.rn8pk0pm4
title: Data from: Phylogenetic inference from atomised 3D morphometric data: a case study using kangaroos

description: 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 discretised using novel approaches to combine the
 objectivity of continuous shape variation for delineating discrete states
 with the model flexibility offered for multi-state characters. This allows
 us to (1) potentially reduce the influence  of non-independence
 among neighbouring landmarks, (2) accommodate multimodal variation from
 saltational evolution, (3) accommodate missing data, such as from
 fragmentary fossils, and (4) promote tree-search efficiency. We built
 discrete morphological character matrices using three alternative
 approaches: commonly used clustering algorithms (UPGMA, *k-*means,
 *k-*medoids, Gaussian mixture modelling), a minimum evolution branch
 length criterion, and a tree sampling procedure. Our phylogenetic analyses
 with these novel matrices generally succeeded in recovering genera and
 several deep-level macropodiform clades, but failed to accurately
 reconstruct intergeneric relationships within the rapid diversification of
 the macropodine sub-family; those relationships were also not recovered
 with continuous morphological data or traditionally discretised characters
 and are the most poorly resolved with DNA data. On balance, our atomised
 characters, which derive from only mandibular and three postcranial
 elements, show promise for improving objectivity, accuracy and
 clocklikeness in morphological phylogenetics and provide pathways for
 accommodating correlated homoplasy and for more accurately estimating
 rates of morphological evolution, and thereby better integrating
 phenotypic and genomic data for phylogenetic inference.
description: # 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 semilandmarks (Subregion_mandible.R; Subregion_scapula.R; Subregion_humerus.R; Subregion_femur.R) #### **raw landmark coordinates:** raw landmark coordinates for the mandible, scapula, humerus and femur. #### **mean rotated landmark coordinates:** Mean rotated landmark coordinates for each subregions of the mandible, scapula, humerus and femur. Each .csv file correspond to a matrix containing landmark coordinates displayed as rows with V1, V2, V3; V4, V5, V6... corresponding to x1, y1, z1; x2, y2, z2... Note that landmark numbers restart from one for each subregion. #### **Scalar characters:** scalar characters for the mandible, scapula, humerus and femur. See supplementary material for more definitions. Units are in mm unless otherwise specified. * `mandible_scalar.csv` *dentaryMaxwidth*: maximum width of the dentary *dentaryMinwidth*: minimum width of the dentary *articular_width*: width of the articular process *articular_length*: length of the articular process *teethwidth*: width of teeth row *teeth_row_height*: height of teeth row *ForamenLength*: length of mandibular foramen *RowWidth_at_m4*: width of teeth row at m4 *Char 31*: Dentary minimum width relative to maximum width *Char 32*: Articular process width relative to its length *Char 33*: Width of the mandibular fovea relative to width of the teeth row behind m4 *Char 34*: Teeth row width relative to its height * `scapula_scalar.csv` *infraspinous_Area*: area of infraspinous fossa (in mm^2^) *supraspinous_Area*: area of supraspinous fossa (in mm^2^) *infra_width*: width of infraspinous fossa *infra_length*: length of supraspinous fossa *infra_width_at_neck*: width of infraspinous fossa at scapular neck *spine_width*: width of scapular spine at neck *glenoid_length*: length of glenoid articular surface *glenoid_length_total*: total length of glenoid *Char 35*: Area (convex hull) of supraspinous (18 landmarks on outline) relative to infraspinous fossa (14 landmarks on outline) *Char 36*: Infraspinous fossa width relative to its length *Char 37:* Spine width at neck relative to infraspinous fossa *Char 38:* Angle at base of scapular spine of line passing by the superior angle and line passing by inferior angle (in degrees) *Char 39*: Angle at scapular neck of line passing by superior border and line passing by coracoid *Char 40:* Glenoid- length of the articular surface relative to total length * `humerus_scalar.csv` *VOL_medTub*: volume of medial tuberosity relative (in mm^3^) *VOL_latTub*: volume of lateral tuberosity (in mm^3^) *olecranonLength*: olecranon fossa length *trochleaLength*: trochlea length *proxdeltoLength*: length of deltoid tuberosity to proximal end of humerus *deltodistL*: length of deltoid tuberosity to distal end of humerus *totalLength*: total humerus length *proxepicondyle_Length*: width of proximal epiphysis *distepicondyle_Length*: width of distal epiphysis *medepiicondyle_Length*: width of medial epicondyle *supinatorLength*: length of the supinator crest *Head_length_sagittal*: length of humeral head in sagittal plane *Head_length_transvers*: length of humeral head in transverse plane *Char 41:* Volume of medial tuberosity relative to volume lateral tuberosity *Char 42:* Olecranon fossa length relative to trochlea length *Char 43:* Extension of deltoid tuberosity relative to the total humerus length *Char 44*: Width of medial epicondyle relative to width of proximal epiphysis *Char 45:* Width of distal epiphysis relative to width of proximal epiphysis *Char 46:* Length of the supinator crest to distal epiphysis relative to total humerus length *Char 47*: Trochlear angle formed by distal extremities and upper middle part in medial view of the humerus *Char 48*: Proximal epiphysis- ratio of length of frontal section relative to sagittal section * `femur_scalar.csv` *troch_length*: trochanteric fossa length *troch_width*: trochanteric fossa width *length_prox.muscle*: length of muscle attachment fovea to the proximal end of the femur *length_muscle.dist*: length of muscle attachment fovea to the distal end of the femur *circonference length*: femur shaft minimum perimeter *TibiaLength* *Char 49*: Trochanteric fossa width relative to its length *Char 50*: Length of muscle attachment fovea to the proximal end relative to total length of the femur *Char 51*: Shaft minimum perimeter relative to total length of the femur *Char 52*: Tibia length relative to femur length ## Software/Code `character_discretisation.R` R script necessary to run the discretization approaches on each of the rotated landmark coordinates for the subregions of the mandible, scapula, humerus and femur (files available in mean rotated landmark coordinates). R 4.2.1 was used to run the analyses using the libraries ape, cluster, ggplot2, ggrepel, mclust, phangorn, shape, vegan.  ## Access Links to other publicly accessible locations of the data: [https://github.com/melinacelik/Phylogenetic-Inference-from-atomised-3D-morphometric-data](https://github.com/melinacelik/Phylogenetic-Inference-from-atomised-3D-morphometric-data)