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

In DrImpute: 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)

DrImpute documentation built on May 2, 2019, 8:31 a.m.