R: Imputing dropout events in single-cell RNA-sequencing data.

DrImpute {DrImpute} | R Documentation

## Imputing dropout events in single-cell RNA-sequencing data.

### Description

Imputing dropout events in single-cell RNA-sequencing data.

### Usage

    DrImpute(X, ks = 10:15, dists = c("spearman", "pearson"), method = "mean",
      cls = NULL, seed = 1, zerop = 0)

### Arguments

`X` | 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"). "eucleadian" can be added as well.
`method` | Use "mean" for mean imputation, "med" for median imputation.
`cls` | User can manually provide clustering information. Using different base clusterings. each row represent different clusterings. each column represent each cell.
`seed` | User can provide a seed.
`zerop` | zero percentage of resulting imputation is at least zerop.

### Value

Imputed Gene expression matrix (gene by cell).

### 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

### Examples

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

[Package DrImpute version 1.0 Index]