In ayurovsky/rnaGinesis: Simulate gene expression data

library(rnaGinesis)
library(ggplot2)
library(reshape)
mu <- rnaGinesis::mu
A <- rnaGinesis::A

a reasonably normal settings, modeling 4 tissues

simresult.a <- simulate_and_test(A_tumor  = A[1:100,1:100],
                               mu_tumor   = mu[1:100],
                               num.sim    = 20,
                               Samplesize  = 100,
                               scaleFactor = rep(30, 3),
                               d.params    = c("Tumor"   = .3,
                                               "Stromal" = .5,
                                               "Immune"  = .1,
                                               "Normal"  = .1),
                               noise_setting = 1.5,
                               seed          = 1234 )

high noise

simresult.b <- simulate_and_test(A_tumor  = A[1:100,1:100],
                               mu_tumor   = mu[1:100],
                               num.sim    = 20,
                               Samplesize  = 100,
                               scaleFactor = rep(30, 3),
                               d.params    = c("Tumor"   = .3,
                                               "Stromal" = .5,
                                               "Immune"  = .1,
                                               "Normal"  = .1),
                               noise_setting = 10,
                               seed          = 1234 )

x.a <- melt(simresult.a[[1]])
x.b <- melt(simresult.b[[1]])
x.a$condition <- "normal noise"
x.b$condition <- "high noise"

mydf <- rbind(x.a,x.b)
mydf<- mydf[,-1]
names(mydf) <- c("tissue","H.RMSE","condition")

p <- ggplot(data = mydf,
            aes(y = H.RMSE,
                x= tissue))
p <- p + geom_violin()
p <- p + geom_jitter(width = 0.1)
p <- p + facet_grid(~condition)
print(p)

x.a <- melt(simresult.a[[4]])
x.b <- melt(simresult.b[[4]])
x.a$condition <- "normal noise"
x.b$condition <- "high noise"

mydf <- rbind(x.a,x.b)
mydf<- mydf[,-1]
names(mydf) <- c("tissue","w_cos_dist","condition")

p <- ggplot(data = mydf,
            aes(y = w_cos_dist,
                x= tissue))
p <- p + geom_violin()
p <- p + geom_jitter(width = 0.1)
p <- p + facet_grid(~condition)
print(p)