True2ObservedCounts: Simulate observed count matrix given technical biases and the...

In YosefLab/SymSim: Simulate Single Cell RNA Sequencing Data

Simulate observed count matrix given technical biases and the true counts

Description

Simulate observed count matrix given technical biases and the true counts

Usage

True2ObservedCounts(
  true_counts,
  meta_cell,
  protocol,
  alpha_mean = 0.1,
  alpha_sd = 0.002,
  gene_len,
  depth_mean,
  depth_sd,
  lenslope = 0.02,
  nbins = 20,
  amp_bias_limit = c(-0.2, 0.2),
  rate_2PCR = 0.8,
  nPCR1 = 16,
  nPCR2 = 10,
  LinearAmp = F,
  LinearAmp_coef = 2000
)

Arguments

true_counts	gene cell matrix
meta_cell	the meta information related to cells, will be combined with technical cell level information and returned
protocol	a string, can be "nonUMI" or "UMI"
alpha_mean	the mean of rate of subsampling of transcripts during capture step, default at 10 percent efficiency
alpha_sd	the std of rate of subsampling of transcripts
gene_len	a vector with lengths of all genes
depth_mean	mean of sequencing depth
depth_sd	std of sequencing depth
lenslope	amount of length bias
nbins	number of bins for gene length
amp_bias_limit	range of amplification bias for each gene, a vector of length ngenes
rate_2PCR	PCR efficiency, usually very high, default is 0.8
nPCR1	the number of PCR cycles in "pre-amplification" step, default is 16
nPCR2	the number of PCR cycles used after fragmentation.
LinearAmp	if linear amplification is used for pre-amplification step, default is FALSE
LinearAmp_coef	the coeficient of linear amplification, that is, how many times each molecule is amplified by

YosefLab/SymSim documentation built on Sept. 30, 2024, 2:22 p.m.