UnSuperClassifier

the data for the clustering. Data should be in the following format: samples in columns and
the genes in the rows (colnames and rownames accordingly). The rownames should be Entrez ID in order to
plot a gene set enrichment analysis.

data

the clinical data provided by the user to plot under the heatmap. it will be
plotted only if show_clin is TRUE. Default value is NULL. see details for format.

clinical_data

The threshold for the PAMR algorithm default is 2.

numeric; Number of genes in each cluster.

TOP_Cluster

numeric; the number of the TOP genes to take from the gene exoression matrix see TopPAM TOP.

A function for unsupervised Clustering of the data

An unsupervised fully-automated pipeline for transcriptome analysis or a supervised option to identify characteristic genes from predefined subclasses.
We rely on the 'pamr' <http://www.bioconductor.org/packages//2.7/bioc/html/pamr.html> clustering algorithm to cluster the Data and then draw a heatmap of the clusters with the most significant genes and the
least significant genes according to the 'pamr' algorithm. This way we get easy to grasp heatmaps that show us for each cluster which are the clusters most defining genes.

UnSuperClassifier: Unsupervised Clustering

Description

Usage

Arguments

Details