make_DEG_data {Corbi} | R Documentation |
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, ... )
n.genes |
The total number of genes in the simulated data. |
n.samples.A |
The number of samples in the group A. |
n.samples.B |
The number of samples in the group B. |
exp.mean |
The mean of log-normal distribution that determines gene-specific expression mean. |
exp.sd |
The standard deviation of log-normal distribution that determines gene-specific expression means. |
alpha |
The dispersion ratio of gene-specific expression standard deviation to mean. |
size.factor.sd |
The standard deviation of size factors for samples. |
... |
The parameters passed to function |
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
.
This function will return a list with the following components:
DEG |
The matrix of simulated DEG pattern, which is generated by |
countsA |
The expression matrix of group A. Each row represents a gene and each column represents a sample. |
countsB |
The expression matrix of group B. Each row represents a gene and each column represents a sample. |