transformation

dists

transformation method: either "pca", "mds", "spectral" or
"spectral_reg", where "spectral_reg" calculates graph Laplacian with
regularization (tau = 1000)

method


All distance matrices are transformed using either principal component 
analysis (PCA), multidimensional scaling (MDS) or by calculating the 
eigenvectors of the graph Laplacian (Spectral). 
The columns of the resulting matrices are then sorted in 
descending order by their corresponding eigenvalues.


Interactive tool for clustering and analysis of single cell RNA-Seq data.

Vladimir Kiselev

Single-Cell Consensus Clustering

transformation function

All distance matrices are transformed using either principal component 
analysis (PCA), multidimensional scaling (MDS) or by calculating the 
eigenvectors of the graph Laplacian (Spectral). 
The columns of the resulting matrices are then sorted in 
descending order by their corresponding eigenvalues.

transformation: Distance matrix transformation

Description

Usage

Arguments

Value