Towards a comprehensive evaluation of dimension reduction methods for transcriptomic data visualization
2022
Haiyang Huang | Yingfan Wang | Cynthia Rudin | Edward P. Browne
The authors provide an evaluation framework for dimension reduction methods that illuminates the strengths and weaknesses of different algorithms, and applies this framework to evaluate the PCA, t-SNE, UMAP, TriMap, PaCMAP, ForceAtlas2, and PHATE algorithms.
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