scSimulator: Single-cell RNA-Seq Tags Simulator

In VCCRI/CIDR: Clustering through Imputation and Dimensionality Reduction

Description

simulates a table of tags generated from a single-cell RNA-Seq experiment.

Usage

scSimulator(N = 3, nDG = 150, nMK = 10, nNDG = 20000, k = 50,
  seed = 17, logmean = 5.25, logsd = 1, v = 9.2)

Arguments

nDG	the number of differentially expressed genes.
nMK	the number of markers (expressed in one cell type only).
nNDG	the number of non-differentially expressed genes.
k	the number of cells in each cell type.
seed	for reproducibility.
logmean	mean of distrubution for each library.
logsd	standard deviation of distribution for each library.
v	dropout level parameter; higher v means a higher level of dropouts.

Value

a list object is returned containing the following components

annotation	0 means a real zero; 1 means a non-zero entry; 2 means a dropout. Note that a dropout may still have a small value.
expectedValues	underlying real expression of the entry.
dropoutsSimulated	expression values after simulation of dropouts before simulation of noise.
tags	the simulated tags after simulation of both dropouts and noise.

Examples

## Generate simulated tags with default parameters: 3 cell types and 50 cells in each cell type.
sData <- scSimulator()
sData$tags[1:5, 1:5]

VCCRI/CIDR documentation built on May 9, 2019, 9:41 p.m.