SimulateCIFs: Simulate Cell Identity Factor Matrix With Lineage Barcodes

In Galaxeee/TedSim: Temporal Dynamics Simulation of scRNA-seq and CRISR/Cas9 lineage barcodes

Simulate Cell Identity Factor Matrix With Lineage Barcodes

Description

Simulate Cell Identity Factor Matrix With Lineage Barcodes

Usage

SimulateCIFs(
  ncells,
  phyla,
  cif_center = 1,
  Sigma = 0.5,
  p_a = 0.8,
  p_edge = NULL,
  n_CIF,
  n_diff,
  step = 1,
  p_d = 0.1,
  mu = 0.1,
  N_char = 9,
  N_ms = 100,
  unif_on = FALSE,
  SIF_res = NULL,
  max_walk = 2,
  lambda = 0.05,
  T_cell = NULL
)

Arguments

ncells	Number of Cells
phyla	Cell state tree
cif_center	Mean of CIFs, default is 1
Sigma	Standard deviation of non-diff CIFs, difault is 0.5
p_a	The asymmetric division rate, default is 0.8
p_edge	The edge transition probability table, default is NULL so that the child edges are chosen with equal possibilities
n_CIF	Total number of SIFs, both non-diff and diff combined
n_diff	Number of diff SIFs
step	Sampling stepsize of diff-SIF Brownian motion
p_d	Dropout rate of CRISPR/Cas9 lineage barcodes
mu	mutation rate of CRISPR/Cas9 lineage barcodes
N_char	number of character sites for CRISPR/Cas9 lineage barcodes
N_ms	number of mutated states for CRISPR/Cas9 lineage barcodes
unif_on	sampling from synthetic uniform-distributed mutated states. When set FALSE, mutated states will be drawn from a real experimental dataset
SIF_res	Optional input for State Identity Factors. If not, the function will generate SIF internally.
max_walk	maximum walk distance of one asymmetric division on the cell state tree
lambda	a num vector that indicates the max and the min value of lambda that weights the additional random walk value
T_cell	optional, a cell division tree

Galaxeee/TedSim documentation built on Oct. 2, 2022, 1:25 a.m.