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 make_DEG_pattern.

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 make_DEG_pattern.

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.


[Package Corbi version 0.6-1 Index]