Generate differentially expressed gene (DEG) data from Gaussian distribution.
make_DEG_data(
n.genes,
n.samples.A,
n.samples.B,
exp.mean = 8,
exp.sd = 2,
alpha = 0.2,
size.factor.sd = 0.1,
...
)The total number of genes in the simulated data.
The number of samples in the group A.
The number of samples in the group B.
The mean of log-normal distribution that determines gene-specific expression mean.
The standard deviation of log-normal distribution that determines gene-specific expression means.
The dispersion ratio of gene-specific expression standard deviation to mean.
The standard deviation of size factors for samples.
The parameters passed to function make_DEG_pattern.
This function will return a list with the following components:
The matrix of simulated DEG pattern, which is generated by make_DEG_pattern.
The expression matrix of group A. Each row represents a gene and each column represents a sample.
The expression matrix of group B. Each row represents a gene and each column represents a sample.
The expression values of each gene are assumed following a Gaussian distribution with
gene-specific mean, which follows a log-normal distribution. The size factor for each
sample follows a Gaussian distribution with zero mean and specific standard deviation.
The heterogeneity of gene expression data is simulated by using the function make_DEG_pattern.