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Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution
Sabrina Renaud1, Anne-Béatrice Dufour1, Emilie A Hardouin2
1Laboratoire de Biométrie et Biologie Evolutive, UMR5558, CNRS, University Lyon 1, 69622 Villeurbanne, France.
Plos One
|July 21, 2015
Summary
Geometric morphometrics uses Principal Component Analysis (PCA) and between-group PCA (bgPCA) to highlight evolutionary "lines of least resistance." Canonical Variate Analysis (CVA) can reveal other differentiation patterns by dampening this effect.
Area of Science:
- Evolutionary Biology
- Quantitative Genetics
- Geometric Morphometrics
Background:
- Geometric morphometrics analyzes complex trait geometry, inherently involving multivariate data.
- Common methods like PCA, CVA, and bgPCA assess patterns of differentiation among specimens.
- CVA standardizes within-group variance, potentially distorting group relationships when variance directions are similar.
Purpose of the Study:
- To investigate how patterns of main variance influence the depiction of among-group differentiation.
- To compare the interpretative outcomes of PCA, bgPCA, and CVA using a case study of house mouse molar shape evolution.
Main Methods:
- Principal Component Analysis (PCA) on the total variance-covariance matrix.
- Canonical Variate Analysis (CVA) to maximize between-group to within-group variance ratio.
- Between-group PCA (bgPCA) to investigate between-group variation without within-group standardization.
Main Results:
- PCA and bgPCA emphasize the role of main variance directions as evolutionary 'lines of least resistance'.
- CVA, by standardizing within-group variance, can obscure these main variance patterns.
- CVA has the potential to reveal alternative differentiation patterns that might be masked by focusing on lines of least resistance.
Conclusions:
- The choice of morphometric method (PCA, bgPCA, or CVA) influences the interpretation of evolutionary differentiation.
- Understanding the impact of variance standardization is crucial for accurate analysis of morphological evolution.
- Different methods highlight distinct aspects of evolutionary processes, offering complementary insights.
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