Tangent Phylogenetic PCA
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- Tangent phylogenetic PCA
Submitted manuscript, 1.15 MB, PDF document
Phylogenetic PCA (p-PCA) is a version of PCA for observations that are leaf nodes of a phylogenetic tree. P-PCA accounts for the fact that such observations are not independent, due to shared evolutionary history. The method works on Euclidean data, but in evolutionary biology there is a need for applying it to data on manifolds, particularly shapes. We provide a generalization of p-PCA to data lying on Riemannian manifolds, called Tangent p-PCA. Tangent p-PCA thus makes it possible to perform dimension reduction on a data set of shapes, taking into account both the non-linear structure of the shape space as well as phylogenetic covariance. We show simulation results on the sphere, demonstrating well-behaved error distributions and fast convergence of estimators. Furthermore, we apply the method to a data set of mammal jaws, represented as points on a landmark manifold equipped with the LDDMM metric.
Original language | English |
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Title of host publication | Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings |
Editors | Rikke Gade, Michael Felsberg, Joni-Kristian Kämäräinen |
Publisher | Springer |
Publication date | 2023 |
Pages | 77-90 |
ISBN (Print) | 9783031314377 |
DOIs | |
Publication status | Published - 2023 |
Event | 23nd Scandinavian Conference on Image Analysis, SCIA 2023 - Lapland, Finland Duration: 18 Apr 2023 → 21 Apr 2023 |
Conference
Conference | 23nd Scandinavian Conference on Image Analysis, SCIA 2023 |
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Land | Finland |
By | Lapland |
Periode | 18/04/2023 → 21/04/2023 |
Series | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13886 LNCS |
ISSN | 0302-9743 |
Bibliographical note
Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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