data_generation: Simulate MAP data set:

In meca7653/MAPTest: MAP Test for detection DE genes

Description

Simulate MAP data set:

Usage

data_generation(G = 100, n_control = 10, n_treat = 10, n_rep = 3,
  k_real = 4, sigma2_r = rep(1, 2), sigma1_2_r = 1,
  sigma2_2_r = c(3, 2), mu1_r = 4, phi_g_r = rep(1, 100),
  p_k_real = c(0.7, 0.1, 0.1, 0.1), x = x)

Arguments

G	Number of genes to simulate
n_control	Number of time points in control group
n_treat	Number of time points in treatment group
n_rep	Number of replicates in both group
k_real	Always be 4
sigma2_r	Variance parameter for τ_{g}
sigma1_2_r	Variance parameter for η_{g1}
sigma2_2_r	Variance parameter for η_{g2}
mu1_r	Mean parameter for η_{g1}
phi_g_r	Dispersion parameter
p_k_real	True proportion for each mixture component
x	Time structured design for the simulated data

Details

The vector of read counts for gene g, treatment group i, replicate j, at time point t,Y_{gij}(t), follows a Negative Binomial distribution parameterized mean λ_{gi} and φ_g, where E[Y_{gij}(t)] = λ_{gi}(t). λ_{gi}(t) is further modeled as λ_{gi}(t) = S_{ij} \exp[η_{g1}I_{i = 2} + B'(t)η_{g2}I_{i = 2} + B'(t)τ_{g}]. We have B'(t) are design matrix, which is constructed by 2 orthorgonal polynomial bases.

• t = 1,..., n_treat (or n_control if control group);

• j = 1,..., n_rep;

• g = 1,...,G; and

• [η_{g1}, η_{g2}, τ_{g}] ~ 4-component gausssian mixture model

Value

• Y1 Simulated data

Examples

library(matlib)
n_basis = 2
n_control = 10
n_treat   = 10
n_rep = 3
tt_treat  = c(1:n_treat)/n_treat
nt = length(tt_treat)
ind_t = sort(sample(c(1:nt), n_control))
tt = tt_treat[ind_t]
tttt = c(rep(tt, n_rep), rep(tt_treat, n_rep))
z = x = matrix(0, length(tttt), n_basis)
z[,1] = 1.224745*tttt
z[,2] = -0.7905694 + 2.371708*tttt^2
x[,1] = z[,1] - Proj(z[,1], rep(1, length(tttt)))
x[,2] = z[,2] - Proj(z[,2], rep(1, length(tttt))) - Proj(z[,2], x[,1])
Y1 = data_generation(G = 100,
                     n_control = n_control,
                     n_treat   = n_treat,
                     n_rep     = n_rep,
                     k_real = 4,
                     sigma2_r = rep(1, 2),
                     sigma1_2_r = 1,
                     sigma2_2_r = c(3,2),
                     mu1_r = 4,
                     phi_g_r = rep(1, 100),
                     p_k_real = c(0.7, 0.1, 0.1, 0.1),
                     x = x)

meca7653/MAPTest documentation built on June 20, 2019, 2 p.m.