init_impute_bulk: Initialize imputation for each individual gene with known...

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 with known dropout rate for each cell type

Usage

init_impute_bulk(Y2, clus, bulk, pg1, cutoff = 0.1, verbose = F)

Arguments

Y2	scRNASeq data matrix. Each row is a gene, each column is a cell.
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.
bulk	Gene expression matrix of bulk RNASeq, only used for plot if verbose = T.
pg1	lower bound of Dropout rate (at least 1- pg1) for each cell type.
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.