README.md

In SamGG/densitycut: An Efficient and Versatile Topological Approach to Clustering Biological Data

densityCut is an efficient density-based clustering algorithm to analyze large-scale biological data. densityCut is written in R, and it has been tested on both Windows 8 and Mac OS X 10.9.5.

After downloading densityCut, it can be installed from the terminal (the dependent packages are listed in DESCRIPTION): R CMD build densitycut_dev/ R CMD install densitycut_0.0.1.tar.gz

The data (variant allele frequencies of somatic mutations, single-cell gene expression data, and single-cell CyTOF data) are in the folder densitycut_dev/data/. After installation densitycut, you can access these data and get help information for these data. For example,

library(densitycut) ?PMF # Get help information for data PMF

cluster.out = DensityCut(PMF$x) # DensityCut clustering analysis col = AssignLabelColor(label=cluster.out$cluster, col=distinct.col) # Assign colour to clusters NeatPlot(x=PMF$x[, 1:2], col=col) # Scatter plots

SamGG/densitycut documentation built on Oct. 30, 2019, 11:48 p.m.