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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| Hlavní autoři: | , , , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Elsevier
2025-01-01
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| Edice: | Computational and Structural Biotechnology Journal |
| Témata: | |
| On-line přístup: | http://www.sciencedirect.com/science/article/pii/S2001037024004136 |
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