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BioRender Template
Principal Component Analysis (PCA) Transformation
Description
This template shows how principal component analysis (PCA) transforms high-dimensional data into a lower-dimensional embedding. On the left, scattered data points in a 3D space with Variable 1, 2, and 3 axes are overlaid with PC1 and PC2 lines, and on the right the same points are replotted in 2D along principal component 1 and 2, with notes that PC1 maximizes variance and PC2 minimizes residuals.
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