Hierarchical Cluster Analysis (HCA)





Select a file *   Example



Optional parameters:


2:Input the column ID (choose one)



Select a file


3:Input the row ID (choose one)



Select a file



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Function:
Hierarchical Cluster Analysis (HCA) is a method of cluster analysis which clusters similar data and seeks to build a hierarchy of clusters. Data in the same cluster represent much more similarity than those in different clusters.


Input:

① Matrix dataset file: the first column is gene names and the first row is sample names.

② Column ID: samples names for the hierarchical cluster analysis. We will use all the samples in the uploaded file for HCA if no information here.

③ Row ID: genes names for the hierarchical cluster analysis. We will use all genes in the uploaded file for HCA if no information here.


Parameters:

None.


Output:

A dendrogram in PDF format and PNG format.

Example:Clustering analysis source files

Samples and indexes of input needs analysis (genes)

z13-15
z14-8
yh2
    
protein-5
POD-10
SOD-5
SOD-10
    


Output


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