Informational rescaling of PCA maps with application to genetic distance

Informational rescaling of PCA maps with application to genetic distance

Principal Component Analysis (PCA) is a powerful multivariate tool allowing the projection of data in low-dimensional representations. Nevertheless, datapoint distances on these low-dimensional projections are challenging to interpret. Here, we propose a computationally simple heuristic to transform...

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Bibliographic Details
Main Authors: Nassim Nicholas Taleb, Pierre Zalloua, Khaled Elbassioni, Haralampos Hatzikirou, Andreas Henschel, Daniel E. Platt
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Computational and Structural Biotechnology Journal
Subjects:
Entropy
Mutual information
Information theory
Genetic distance
Genetic maps
Online Access:http://www.sciencedirect.com/science/article/pii/S2001037024004136
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http://www.sciencedirect.com/science/article/pii/S2001037024004136

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