Nothing
## Example code used in the vignette, but not executed there.
## This can use memory rather quickly. You might want to rm objects and
## gc().
library(OncoSimulR)
rm(list = ls()); gc()
ng <- 10000
u <- allFitnessEffects(noIntGenes = c(rep(0.1, ng/2), rep(-0.1, ng/2)))
t_e_10000 <- system.time(e_10000 <- oncoSimulPop(5,
u,
model = "Exp",
mu = 1e-7,
detectionSize = 1e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
mutationPropGrowth = TRUE,
mc.cores = 1
))
t_e_10000
summary(e_10000)[, c(1:3, 8, 9)]
print(object.size(e_10000), units = "MB")
t_e_10000b <- system.time(e_10000b <- oncoSimulPop(5,
u,
model = "Exp",
mu = 1e-7,
detectionSize = 1e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
keepEvery = NA,
mutationPropGrowth = TRUE,
mc.cores = 1
))
t_e_10000b
summary(e_10000b)[, c(1:3, 8, 9)]
print(object.size(e_10000b), units = "MB")
rm(list = ls()); gc()
ng <- 50000
u <- allFitnessEffects(noIntGenes = c(rep(0.1, ng/2), rep(-0.1, ng/2)))
t_e_50000 <- system.time(e_50000 <- oncoSimulPop(5,
u,
model = "Exp",
mu = 1e-7,
detectionSize = 1e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
keepEvery = NA,
mutationPropGrowth = FALSE,
mc.cores = 1
))
t_e_50000
summary(e_50000)[, c(1:3, 8, 9)]
print(object.size(e_50000), units = "MB")
rm(list = ls()); gc()
ng <- 50000
u <- allFitnessEffects(noIntGenes = c(rep(0.1, ng/2), rep(-0.1, ng/2)))
t_e_50000np <- system.time(e_50000np <- oncoSimulPop(5,
u,
model = "Exp",
mu = 1e-7,
detectionSize = 1e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
keepEvery = 1,
mutationPropGrowth = FALSE,
mc.cores = 1
))
t_e_50000np
summary(e_50000np)[, c(1:3, 8, 9)]
print(object.size(e_50000np), units = "MB")
rm(list = ls()); gc()
ng <- 50000
u <- allFitnessEffects(noIntGenes = c(rep(0.1, ng/2), rep(-0.1, ng/2)))
t_e_50000c <- system.time(e_50000c <- oncoSimulPop(5,
u,
model = "Exp",
mu = 1e-7,
detectionSize = 1e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
keepEvery = NA,
mutationPropGrowth = TRUE,
mc.cores = 1
))
t_e_50000c
summary(e_50000c)[, c(1:3, 8, 9)]
print(object.size(e_50000c), units = "MB")
#### McFL
rm(list = ls()); gc()
ng <- 50000
u <- allFitnessEffects(noIntGenes = c(rep(0.1, ng/2), rep(-0.1, ng/2)))
t_mc_50000_nmpg <- system.time(mc_50000_nmpg <- oncoSimulPop(5,
u,
model = "McFL",
mu = 1e-7,
detectionSize = 1e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
keepEvery = NA,
mutationPropGrowth = FALSE,
mc.cores = 1
))
t_mc_50000_nmpg
summary(mc_50000_nmpg)[, c(1:3, 8, 9)]
print(object.size(mc_50000_nmpg), units = "MB")
rm(list = ls()); gc()
ng <- 50000
u <- allFitnessEffects(noIntGenes = c(rep(0.1, ng/2), rep(-0.1, ng/2)))
t_mc_50000_nmpg_k <- system.time(mc_50000_nmpg_k <- oncoSimulPop(5,
u,
model = "McFL",
mu = 1e-7,
detectionSize = 1e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
keepEvery = 1,
mutationPropGrowth = FALSE,
mc.cores = 1
))
t_mc_50000_nmpg_k
summary(mc_50000_nmpg_k)[, c(1:3, 8, 9)]
print(object.size(mc_50000_nmpg_k), units = "MB")
rm(list = ls()); gc()
ng <- 50000
u <- allFitnessEffects(noIntGenes = c(rep(0.1, ng/2), rep(-0.1, ng/2)))
t_mc_50000_nmpg_3e6 <- system.time(mc_50000_nmpg_3e6 <- oncoSimulPop(5,
u,
model = "McFL",
mu = 1e-7,
detectionSize = 3e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
keepEvery = NA,
mutationPropGrowth = FALSE,
mc.cores = 1
))
t_mc_50000_nmpg_3e6
summary(mc_50000_nmpg_3e6)[, c(1:3, 8, 9)]
print(object.size(mc_50000_nmpg_3e6), units = "MB")
rm(list = ls()); gc()
ng <- 50000
u <- allFitnessEffects(noIntGenes = c(rep(0.1, ng/2), rep(-0.1, ng/2)))
t_mc_50000_nmpg_5mu <- system.time(mc_50000_nmpg_5mu <- oncoSimulPop(5,
u,
model = "McFL",
mu = 5e-7,
detectionSize = 1e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
keepEvery = NA,
mutationPropGrowth = FALSE,
mc.cores = 1
))
t_mc_50000_nmpg_5mu
summary(mc_50000_nmpg_5mu)[, c(1:3, 8, 9)]
print(object.size(mc_50000_nmpg_5mu), units = "MB")
rm(list = ls()); gc()
ng <- 50000
u <- allFitnessEffects(noIntGenes = c(rep(0.1, ng/2), rep(-0.1, ng/2)))
t_mc_50000_nmpg_5mu_k <- system.time(mc_50000_nmpg_5mu_k <- oncoSimulPop(5,
u,
model = "McFL",
mu = 5e-7,
detectionSize = 1e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
keepEvery = 1,
mutationPropGrowth = FALSE,
mc.cores = 1
))
t_mc_50000_nmpg_5mu_k
summary(mc_50000_nmpg_5mu_k)[, c(1:3, 8, 9)]
print(object.size(mc_50000_nmpg_5mu_k), units = "MB")
rm(list = ls()); gc()
ng <- 50000
u <- allFitnessEffects(noIntGenes = c(rep(0.1, ng/2), rep(-0.1, ng/2)))
t_mc_50000 <- system.time(mc_50000 <- oncoSimulPop(5,
u,
model = "McFL",
mu = 1e-7,
detectionSize = 1e6,
detectionDrivers = NA,
detectionProb = NA,
keepPhylog = TRUE,
onlyCancer = FALSE,
keepEvery = NA,
mutationPropGrowth = TRUE,
mc.cores = 1
))
t_mc_50000
summary(mc_50000)[, c(1:3, 8, 9)]
print(object.size(mc_50000), units = "MB")
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