makeFCMatrix: Generate the fold change matrix for simulating count data

In TCC: TCC: Differential expression analysis for tag count data with robust normalization strategies

Description

Generate the fold change matrix for simulating count data under the Gammma distribution

Usage

makeFCMatrix(Ngene = 10000, PDEG = 0.20, DEG.assign = NULL,
             replicates = NULL, fc.params = NULL)

Arguments

Ngene	numeric scalar specifying the number of genes.
PDEG	numeric scalar specifying the proportion of differentially expressed genes (DEGs).
DEG.assign	numeric vector specifying the proportion of DEGs up- or down-regulated in individual groups to be compared. The number of elements should be the same as that of replicates if replicates is specified. The indication of replicates means a single-factor experimental design.
replicates	numeric vector indicating the numbers of (biological) replicates for individual groups compared. Ignored if group is specified.
fc.params	foldchanges of DEGs are randomly sampled from f + Γ(a, b) where a is a shape and b is a scale of Gamma distribution. The default values are f = 1.2, a = 2, and b = 0.5

Details

makeFCMatrix function is a function for generating the foldchanges of DEGs. The foldchanges are randomly sampled from f + Γ(a, b) where a is a shape and b is a scale of Gamma distribution.

Value

matrix

Examples

fc.matrix <- makeFCMatrix()

TCC documentation built on Nov. 8, 2020, 8:20 p.m.