init_impute: Initialize imputation for each individual gene

In JunLiuLab/SIMPLEs: SIMPLEs: single-cell RNA sequencing imputation and cell clustering methods by modeling gene module variation

Description

Initialize imputation for each individual gene

Usage

init_impute(Y2, M0, clus, p_min = 0.6, cutoff = 0.1, verbose = F)

Arguments

Y2	scRNASeq data matrix. Each row is a gene, each column is a cell.
M0	number of cell types
clus	A numeric vector for the cell type labels of cells in the scRNASeq. The labels must start from 1 to the number of types (M0).
p_min	Restrict the max dropout rate to be 1-p_min. Default = 0.6.
cutoff	The value below cutoff is treated as no expression. Default = 0.1.
verbose	Whether to plot some intermediate result. Default = False.

Details

Fit each gene expression by a zero-inflated censored Gaussian distribution and return a random sample of imputed values for initialization

Value

Imputed gene expression matrix, treat each gene independently

Author(s)

Zhirui Hu, [e-mail]

Songpeng Zu, [e-mail]

JunLiuLab/SIMPLEs documentation built on March 18, 2021, 3:10 a.m.