Data Processing Datacheck Filter Normalize Baseline Drug Resistance SNR CD-Ratio △CD-Ratio Rarefaction Analysis Alpha index Beta index Multivariate Analysis Unsupervised classification PCA PCoA Supervised classification SVM PLS-DA SPLS-DA Heatmap RandomForest Hierarchical cluster Deep Learning Biomarker Selection Imp.PLS-DA Imp.SPLS-DA Imp.RandomForest Network Analysis Interaction network Download Exit

Hierarchical Cluster Analysis:

       Hierarchical cluster analysis (HCA from now on) is a clustering method in which "distances" between samples are calculated and displayed in a dendrogram (a tree-like structure; these are also used in evolution and systematics where they are called cladograms). The details behind HCA can be readily found elsewhere.You have access to any of the methods available for computing distances between samples and any of the methods for identifying clusters.

method:

Without pca With pca

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