BASiCS_Sim: Generates synthetic data according to the model implemented...
In BASiCS: Bayesian Analysis of Single-Cell Sequencing data

Description Usage Arguments Value Author(s) References Examples

BASiCS_Sim creates a simulated dataset from the model implemented in BASiCS.

1	BASiCS_Sim(Mu, Mu_spikes = NULL, Delta, Phi = NULL, S, Theta, BatchInfo = NULL)

`Mu`	Gene-specific mean expression parameters μ_i for all biological genes (vector of length `q.bio`, all elements must be positive numbers)
`Mu_spikes`	μ_i for all technical genes defined as true input molecules (vector of length `q-q.bio`, all elements must be positive numbers). If `Mu_spikes = NULL`, the generated data will not contain spike-ins. If `Phi = NULL`, `Mu_spikes` will be ignored. Default: `Mu_spikes = NULL`.
`Delta`	Gene-specific biological over-dispersion parameters δ_i, biological genes only (vector of length `q.bio`, all elements must be positive numbers)
`Phi`	Cell-specific mRNA content normalising parameters φ_j (vector of length `n`, all elements must be positive numbers and the sum of its elements must be equal to `n`). `Phi` must be set equal to `NULL` when generating data without spike-ins. If `Mu_spikes = NULL`, `Phi` will be ignored. Default: `Phi = NULL`
`S`	Cell-specific technical normalising parameters s_j (vector of length `n`, all elements must be positive numbers)
`Theta`	Technical variability parameter θ (must be positive). `Theta` can be a scalar (single batch of samples), or a vector (multiple batches of samples). If a value for `BatchInfo` is provided, the length of `Theta` must match the number of unique values in `BatchInfo`.
`BatchInfo`	Vector detailing which batch each cell should be simulated from. If spike-ins are not in use, the number of unique values contained in `BatchInfo` must be larger than 1 (i.e. multiple batches are present).

An object of class SingleCellExperiment, including synthetic data generated by the model implemented in BASiCS.

Catalina A. Vallejos cnvallej@uc.cl, Nils Eling

Vallejos, Marioni and Richardson (2015). PLoS Computational Biology.

# Simulated parameter values for 10 genes
# (7 biogical and 3 spike-in) measured in 5 cells
Mu <- c(8.36, 10.65, 4.88, 6.29, 21.72, 12.93, 30.19)
Mu_spikes <-  c(1010.72, 7.90, 31.59)
Delta <- c(1.29, 0.88, 1.51, 1.49, 0.54, 0.40, 0.85)
Phi <- c(1.00, 1.06, 1.09, 1.05, 0.80)
S <- c(0.38, 0.40, 0.38, 0.39, 0.34)
Theta <- 0.39

# Data with spike-ins, single batch
Data <- BASiCS_Sim(Mu, Mu_spikes, Delta, Phi, S, Theta)
head(SingleCellExperiment::counts(Data))
dim(SingleCellExperiment::counts(Data))
altExp(Data)
rowData(altExp(Data))

# Data with spike-ins, multiple batches
BatchInfo <- c(1,1,1,2,2)
Theta2 <- rep(Theta, times = 2)
Data <- BASiCS_Sim(Mu, Mu_spikes, Delta, Phi, S, Theta2, BatchInfo)

# Data without spike-ins, multiple batches
Data <- BASiCS_Sim(Mu, Mu_spikes = NULL, Delta, 
                   Phi = NULL, S, Theta2, BatchInfo)