make_DEG_data2 {Corbi} | R Documentation |
Simulate differentially expressed gene data (Negative binomial)
Description
Generate differentially expressed gene (DEG) data from negative binomial distribution.
Usage
make_DEG_data2(
n.genes,
n.samples.A,
n.samples.B,
exp.mean = 8,
exp.sd = 2,
dispersion = NULL,
size.factor.sd = 0.1,
...
)
Arguments
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 mean. |
dispersion |
The dispersion parameter for negative binomial distribution. The default values are determined by the expression mean. |
size.factor.sd |
The standard deviation of size factors for samples. |
... |
The parameters passed to function |
Details
The expression values of each gene are assumed following a negative binomial 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
.
Value
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. |