BioinformaticsCell ReportsPeer-reviewed
Dimensionality reduction by UMAP reinforces sample heterogeneity analysis in bulk transcriptomic data
Yang Yang, Hongjian Sun, Yu Zhang…·Di Yu
This study compares dimensionality reduction methods for bulk transcriptomic data, finding UMAP better preserves sample neighbourhood and clustering accuracy than PCA, MDS, and t-SNE.
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