UnSuperClassifier: Unsupervised Clustering

Description Usage Arguments Details

View source: R/UnSuperClassifier.R

Description

A function for unsupervised Clustering of the data

Usage

1
UnSuperClassifier(data,clinical_data=NULL,thr=2,TOP_Cluster=150,TOP=100)

Arguments

data

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.

clinical_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.

thr

The threshold for the PAMR algorithm default is 2.

TOP_Cluster

numeric; Number of genes in each cluster.

TOP

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

Details

sample data should be a data.frame with the sample names as rownames and the clinical triats as columns. each trait must be a numeric variable. @return the function is an autated Pipeline for clustering it plot cluster analysis for the geneset


AutoPipe documentation built on May 1, 2019, 7:28 p.m.