R: get base clustering results using SC3 based clustering...

getCls {DrImpute} | R Documentation

## get base clustering results using SC3 based clustering methods.

### Description

Similarity matrix constructed using "pearson", "spearman" or "euclidean". K-means clustering is performed on first few number of principal components of similarity matrix.

### Usage

    getCls(X, ks = 10:15, dists = c("spearman", "pearson"),
      dim.reduc.prop = 0.05)

### Arguments

`X` | Log transformed gene expression matrix (Gene by Cell).
`ks` | Number of cell clustering groups. Default set to ks = 10:15.
`dists` | Distribution matrices to use. Default is set to c("spearman", "pearson"). "euclidean" can be added as well.
`dim.reduc.prop` | Proportion of principal components to use for K-means clustering.

### Value

A matrix object, Each row represent different clustering results.

### Author(s)

Il-Youp Kwak

### References

Il-Youp Kwak, Wuming Gong, Kaoko Koyano-Nakagawa and Daniel J. Garry (2017+) DrImpute: Imputing dropout eveents in single cell RNA sequencing data

### See Also

`DrImpute` `preprocessSC`

### Examples

    data(exdata)
    exdata <- preprocessSC(exdata)
    exdata <- exdata[1:3000, 1:80]
    logdat <- log(exdata+1)
    cls <- getCls(logdat)

[Package DrImpute version 1.0 Index]