Use hierarchical clustering to group cancer types together by average miRNA expression.
Hierarchical clustering orders samples by similarity of features, which here are average miRNA expression levels. The closeness of similarity is shown in the dendrogram.
Provide a list of miRNAs to use in clustering in the text box, or check the box to use all available miRNAs.
The results are expressed visually as a heat map, which can be shown as gradients of the color options.
Mean-based scaling of expression values within samples is highly recommended, but can be turned off.
The dendrogram can be cut to create clusters of patients.
miRNAs can be excluded on the basis of mean expression or standard deviation of expression throughout the dataset.
Use the minimum/maximum values to set the filter limits.