Skip to main content
Journal cover image

Development and Assessment of Fully Automated and Globally Transitive Geometric Morphometric Methods, With Application to a Biological Comparative Dataset With High Interspecific Variation.

Publication ,  Journal Article
Gao, T; Yapuncich, GS; Daubechies, I; Mukherjee, S; Boyer, DM
Published in: Anatomical record (Hoboken, N.J. : 2007)
April 2018

Automated geometric morphometric methods are promising tools for shape analysis in comparative biology, improving researchers' abilities to quantify variation extensively (by permitting more specimens to be analyzed) and intensively (by characterizing shapes with greater fidelity). Although use of these methods has increased, published automated methods have some notable limitations: pairwise correspondences are frequently inaccurate and pairwise mappings are not globally consistent (i.e., they lack transitivity across the full sample). Here, we reassess the accuracy of published automated methods-cPDist (Boyer et al. Proc Nat Acad Sci 108 () 18221-18226) and auto3Dgm (Boyer et al.: Anat Rec 298 () 249-276)-and evaluate several modifications to these methods. We show that a substantial percentage of alignments and pairwise maps between specimens of dissimilar geometries were inaccurate in the study of Boyer et al. (Proc Nat Acad Sci 108 () 18221-18226), despite a taxonomically partitioned variance structure of continuous Procrustes distances. We show these inaccuracies are remedied using a globally informed methodology within a collection of shapes, rather than relying on pairwise comparisons (c.f. Boyer et al.: Anat Rec 298 () 249-276). Unfortunately, while global information generally enhances maps between dissimilar objects, it can degrade the quality of correspondences between similar objects due to the accumulation of numerical error. We explore a number of approaches to mitigate this degradation, quantify their performance, and compare the generated pairwise maps (and the shape space characterized by these maps) to a "ground truth" obtained from landmarks manually collected by geometric morphometricians. Novel methods both improve the quality of the pairwise correspondences relative to cPDist and achieve a taxonomic distinctiveness comparable to auto3Dgm. Anat Rec, 301:636-658, 2018. © 2017 Wiley Periodicals, Inc.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Anatomical record (Hoboken, N.J. : 2007)

DOI

EISSN

1932-8494

ISSN

1932-8486

Publication Date

April 2018

Volume

301

Issue

4

Start / End Page

636 / 658

Related Subject Headings

  • Imaging, Three-Dimensional
  • Datasets as Topic
  • Animals
  • Anatomy & Morphology
  • 3104 Evolutionary biology
  • 3101 Biochemistry and cell biology
  • 11 Medical and Health Sciences
  • 06 Biological Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Gao, T., Yapuncich, G. S., Daubechies, I., Mukherjee, S., & Boyer, D. M. (2018). Development and Assessment of Fully Automated and Globally Transitive Geometric Morphometric Methods, With Application to a Biological Comparative Dataset With High Interspecific Variation. Anatomical Record (Hoboken, N.J. : 2007), 301(4), 636–658. https://doi.org/10.1002/ar.23700
Gao, Tingran, Gabriel S. Yapuncich, Ingrid Daubechies, Sayan Mukherjee, and Doug M. Boyer. “Development and Assessment of Fully Automated and Globally Transitive Geometric Morphometric Methods, With Application to a Biological Comparative Dataset With High Interspecific Variation.Anatomical Record (Hoboken, N.J. : 2007) 301, no. 4 (April 2018): 636–58. https://doi.org/10.1002/ar.23700.
Gao T, Yapuncich GS, Daubechies I, Mukherjee S, Boyer DM. Development and Assessment of Fully Automated and Globally Transitive Geometric Morphometric Methods, With Application to a Biological Comparative Dataset With High Interspecific Variation. Anatomical record (Hoboken, NJ : 2007). 2018 Apr;301(4):636–58.
Gao, Tingran, et al. “Development and Assessment of Fully Automated and Globally Transitive Geometric Morphometric Methods, With Application to a Biological Comparative Dataset With High Interspecific Variation.Anatomical Record (Hoboken, N.J. : 2007), vol. 301, no. 4, Apr. 2018, pp. 636–58. Epmc, doi:10.1002/ar.23700.
Gao T, Yapuncich GS, Daubechies I, Mukherjee S, Boyer DM. Development and Assessment of Fully Automated and Globally Transitive Geometric Morphometric Methods, With Application to a Biological Comparative Dataset With High Interspecific Variation. Anatomical record (Hoboken, NJ : 2007). 2018 Apr;301(4):636–658.
Journal cover image

Published In

Anatomical record (Hoboken, N.J. : 2007)

DOI

EISSN

1932-8494

ISSN

1932-8486

Publication Date

April 2018

Volume

301

Issue

4

Start / End Page

636 / 658

Related Subject Headings

  • Imaging, Three-Dimensional
  • Datasets as Topic
  • Animals
  • Anatomy & Morphology
  • 3104 Evolutionary biology
  • 3101 Biochemistry and cell biology
  • 11 Medical and Health Sciences
  • 06 Biological Sciences