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library(gridExtra)
library(reshape2)
library(lubridate)
library(tidyverse)
setwd("~/Dropbox/Emory Courses/DOHG/")
###### Predefined global parameter
#' Number of simulations, number of subjects, Number of phenotypes and MAF
#' (independent of covariates)
Nsub_array <- c(500)
Npheno_array <- c(4, 6, 8, 10, 12)
maf_array <- 0.25
gamma_array <- c(0.15, 0.25, 0.35)
delta_array <- c(0.5, 0.75, 1)
delta_select_array <- c(0.25, 0.5, 0.75, 1)
Nsim <- 1000
param_comb <- expand.grid(Nsub = Nsub_array,
Npheno = Npheno_array,
maf = maf_array,
gamma = gamma_array,
delta = delta_array,
delta_select = delta_select_array)
full_df <- data.frame()
for (array.id in 1:nrow(param_comb)) {
Nsub <- param_comb[array.id, "Nsub"]
Npheno <- param_comb[array.id, "Npheno"]
maf <- param_comb[array.id, "maf"]
gamma <- param_comb[array.id, "gamma"]
delta <- param_comb[array.id, "delta"]
delta_select <- param_comb[array.id, "delta_select"]
file_SMAT_time <- paste("time", "SMAT_time", "adj", "dglm", Nsim, "subj", Nsub, "pheno", Npheno, "MAF", maf, "Gamma", gamma, "Delta", delta, "DeltaSelect", delta_select, sep = "_")
file_CCT_time <- paste("time", "CCT_time", "adj", "dglm", Nsim, "subj", Nsub, "pheno", Npheno, "MAF", maf, "Gamma", gamma, "Delta", delta, "DeltaSelect", delta_select, sep = "_")
file_includeXsquare_CCT_time <- paste("time", "includeXsquare_CCT_time", "adj", "dglm", Nsim, "subj", Nsub, "pheno", Npheno, "MAF", maf, "Gamma", gamma, "Delta", delta, "DeltaSelect", delta_select, sep = "_")
file_simulation_time <- paste("time", "simulation_time", "adj", "dglm", Nsim, "subj", Nsub, "pheno", Npheno, "MAF", maf, "Gamma", gamma, "Delta", delta, "DeltaSelect", delta_select, sep = "_")
file_name_SMAT_pvalue <- paste("pvalue", "SMAT", "adj", "dglm", Nsim, "subj", Nsub, "pheno", Npheno, "MAF", maf, "Gamma", gamma, "Delta", delta, "DeltaSelect", delta_select, sep = "_")
file_name_CCT_pvalue <- paste("pvalue", "CCT", "adj", "dglm", Nsim, "subj", Nsub, "pheno", Npheno, "MAF", maf, "Gamma", gamma, "Delta", delta, "DeltaSelect", delta_select, sep = "_")
file_name_includeXsquare_CCT_pvalue <- paste("pvalue", "includeXsquare_CCT", "adj", "dglm", Nsim, "subj", Nsub, "pheno", Npheno, "MAF", maf, "Gamma", gamma, "Delta", delta, "DeltaSelect", delta_select, sep = "_")
assign(file_SMAT_time,
get(load(paste("Result/New_4_6_Power_Simulation/", file_SMAT_time, ".RData", sep = ""))))
assign(file_CCT_time,
get(load(paste("Result/New_4_6_Power_Simulation/", file_CCT_time, ".RData", sep = ""))))
assign(file_includeXsquare_CCT_time,
get(load(paste("Result/New_4_6_Power_Simulation/", file_includeXsquare_CCT_time, ".RData", sep = ""))))
assign(file_simulation_time,
get(load(paste("Result/New_4_6_Power_Simulation/", file_simulation_time, ".RData", sep = ""))))
assign(file_name_SMAT_pvalue,
get(load(paste("Result/New_4_6_Power_Simulation/", file_name_SMAT_pvalue, ".RData", sep = ""))))
assign(file_name_CCT_pvalue,
get(load(paste("Result/New_4_6_Power_Simulation/", file_name_CCT_pvalue, ".RData", sep = ""))))
assign(file_name_includeXsquare_CCT_pvalue,
get(load(paste("Result/New_4_6_Power_Simulation/", file_name_includeXsquare_CCT_pvalue, ".RData", sep = ""))))
temp_DF <- data.frame(
"Nsub" = Nsub,
"Npheno" = Npheno,
"maf" = maf,
"gamma" = gamma,
"delta" = delta,
"delta_select" = delta_select,
"SMAT" = get(load(paste("Result/New_4_6_Power_Simulation/", file_name_SMAT_pvalue, ".RData", sep = ""))),
"CCT" = get(load(paste("Result/New_4_6_Power_Simulation/", file_name_CCT_pvalue, ".RData", sep = ""))),
"CCT_includeXsquare" = get(load(paste("Result/New_4_6_Power_Simulation/", file_name_includeXsquare_CCT_pvalue, ".RData", sep = "")))
# "SMAT_Time" = get(load(paste("Result/New_4_6_Power_Simulation/", file_SMAT_time, ".RData", sep = ""))),
# "CCT_Time" = get(load(paste("Result/New_4_6_Power_Simulation/", file_CCT_time, ".RData", sep = ""))),
# "CCT_includeXsquare_Time" = get(load(paste("Result/New_4_6_Power_Simulation/", file_includeXsquare_CCT_time, ".RData", sep = ""))),
# "Overall_Time" = get(load(paste("Result/New_4_6_Power_Simulation/", file_simulation_time, ".RData", sep = "")))
)
full_df <- rbind(full_df, temp_DF)
}
names(full_df)
table(full_df$maf)
full_df %>%
filter(Npheno_array == 4,
delta_array == 0.5,
delta_select_array == 0.25,
gamma_array == 0.15)
full_df %>%
filter(Npheno == 4,
delta == 0.5,
delta_select == 0.25,
gamma == 0.15)
table(full_df$SMAT)
gamma_015 <-
full_df %>%
filter(Npheno == 4,
delta == 0.5,
delta_select == 0.25,
gamma == 0.15)
head(gamma_015)
gamma_025 <-
full_df %>%
filter(Npheno == 4,
delta == 0.5,
delta_select == 0.25,
gamma == 0.25)
gamma_035 <-
full_df %>%
filter(Npheno == 4,
delta == 0.5,
delta_select == 0.25,
gamma == 0.35)
sum(gamma_015$SMAT <= 0.05/40000)
sum(gamma_015$SMAT <= 0.05/20000)
gamma_015 <-
full_df %>%
filter(Npheno == 8,
delta == 0.5,
delta_select == 0.25,
gamma == 0.15)
sum(gamma_015$SMAT <= 0.05/20000)
gamma_015 <-
full_df %>%
filter(Npheno == 8,
delta == 0.5,
delta_select == 0.75,
gamma == 0.15)
sum(gamma_015$SMAT <= 0.05/20000)
gamma_015$SMAT <= 0.05/20000
gamma_015 <-
full_df %>%
filter(Npheno == 8,
delta == 0.5,
delta_select == 0.75,
gamma == 0.15)
sum(gamma_015$SMAT <= 0.05/20000)
sum(gamma_015$SMAT <= 0.05)
gamma_015 <-
full_df %>%
filter(Npheno == 8,
delta == 1,
delta_select == 0.75,
gamma == 0.15)
sum(gamma_015$SMAT <= 0.05)
gamma_015 <-
full_df %>%
filter(Npheno == 8,
delta == 1,
delta_select == 0.75,
gamma == 0.15)
sum(gamma_015$SMAT <= 0.05/50000)
gamma_025 <-
full_df %>%
filter(Npheno == 8,
delta == 1,
delta_select == 0.75,
gamma == 0.25)
sum(gamma_025$SMAT <= 0.05/50000)
gamma_035 <-
full_df %>%
filter(Npheno == 8,
delta == 1,
delta_select == 0.75,
gamma == 0.35)
sum(gamma_035$SMAT <= 0.05/50000)
mean(gamma_015$SMAT)
mean(gamma_025$SMAT) # 0.0134313
mean(gamma_035$SMAT) # 0.0134313
gamma_035$SMAT
specify_decimal <- function(x, k) trimws(format(round(x, k), nsmall=k))
specify_decimal(mean(gamma_025$SMAT), 20)
specify_decimal(mean(gamma_015$SMAT), 20)
specify_decimal(mean(gamma_035$SMAT), 20) # 0.0134313
specify_decimal(mean(gamma_015$CCT), 20) # 0.01343130059667276693
specify_decimal(mean(gamma_025$CCT), 20) # 0.01343130059667275132
specify_decimal(mean(gamma_035$CCT), 20)
specify_decimal(mean(gamma_015$CCT_includeXsquare), 20) # 0.00043311829323283403
specify_decimal(mean(gamma_025$CCT_includeXsquare), 20) # 0.00034450325588403154
specify_decimal(mean(gamma_035$CCT_includeXsquare), 20) # 0.00034450325588407350
specify_decimal(median(gamma_015$SMAT), 20) # 0.01343130059667276693
specify_decimal(median(gamma_015$CCT), 20) # 0.00043311829323283403
1.122445e-05
specify_decimal(median(gamma_015$CCT_includeXsquare), 20) # 0.00034450325588403154
specify_decimal(median(gamma_025$SMAT), 20) # 0.00247922534895639313
specify_decimal(median(gamma_025$CCT), 20)
specify_decimal(median(gamma_025$CCT_includeXsquare), 20) # 0.0000008520913
specify_decimal(median(gamma_035$SMAT), 20) # 0.00247922534895639313
specify_decimal(median(gamma_035$CCT), 20) # 0.00001122445
specify_decimal(median(gamma_035$CCT_includeXsquare), 20) # 0.0000008520913
specify_decimal(max(gamma_015$SMAT), 20) # 0.00247922534895639313
specify_decimal(max(gamma_015$CCT), 20) # 0.00001122445
specify_decimal(max(gamma_015$CCT_includeXsquare), 20) # 0.0000008520913
specify_decimal(max(gamma_025$SMAT), 20) # 0.00247922534895639313
specify_decimal(max(gamma_025$CCT), 20) # 0.00001122445
specify_decimal(max(gamma_025$CCT_includeXsquare), 20) # 0.0000008520913
specify_decimal(max(gamma_015$SMAT), 20) # 0.00247922534895639313
specify_decimal(max(gamma_015$CCT), 20) # 0.00001122445
specify_decimal(max(gamma_015$CCT_includeXsquare), 20)
specify_decimal(max(gamma_025$SMAT), 20) # 0.00247922534895639313
specify_decimal(max(gamma_025$CCT), 20)
specify_decimal(max(gamma_025$CCT_includeXsquare), 20)
specify_decimal(max(gamma_035$SMAT), 20) # 0.00247922534895639313
specify_decimal(max(gamma_035$CCT), 20)
specify_decimal(max(gamma_035$CCT_includeXsquare), 20)
median(gamma_015$SMAT)==median(gamma_025$SMAT)
median(gamma_015$SMAT)==median(gamma_035$SMAT)
max(gamma_035$CCT)==max(gamma_025$CCT)
specify_decimal(min(gamma_015$SMAT), 20) # 0.48949447667456835731
specify_decimal(min(gamma_015$CCT), 20) # 0.02737312842337480401
specify_decimal(min(gamma_015$CCT_includeXsquare), 20) # 0.07169513212008116199
specify_decimal(min(gamma_025$SMAT), 20) # 0.48949447667455991962
specify_decimal(min(gamma_025$CCT), 20) # 0.02737312842337469299
specify_decimal(min(gamma_025$CCT_includeXsquare), 20) # 0.07169513212008526981
specify_decimal(min(gamma_015$CCT_includeXsquare), 20)
specify_decimal(min(gamma_025$CCT_includeXsquare), 20)
gamma_025[which.min(gamma_025$CCT_includeXsquare),]
gamma_015[which.min(gamma_015$CCT_includeXsquare),]
dim(gamma_025)
gamma_025[which.min(gamma_025$CCT_includeXsquare),]
specify_decimal(min(gamma_035$SMAT), 20) # 0.48949447667456946753
specify_decimal(min(gamma_035$CCT), 20) # 0.02737312842337469299
specify_decimal(min(gamma_035$CCT_includeXsquare), 20) # 0.07169513212008515879
gamma_015 <-
full_df %>%
filter(Npheno == 12,
delta == 1,
delta_select == 0.75,
gamma == 0.15)
sum(gamma_015$SMAT <= 0.05/50000) # 7
specify_decimal(mean(gamma_015$SMAT), 20) # 0.01343130059667276693
specify_decimal(mean(gamma_015$CCT), 20) # 0.00043311829323283403
specify_decimal(mean(gamma_015$CCT_includeXsquare), 20) # 0.00034450325588403154
gamma_025 <-
full_df %>%
filter(Npheno == 12,
delta == 1,
delta_select == 0.75,
gamma == 0.25)
sum(gamma_025$SMAT <= 0.05/50000) # 7
specify_decimal(mean(gamma_025$SMAT), 20) # 0.01343130059667275132
specify_decimal(mean(gamma_025$CCT), 20) # 0.00043311829323283468
specify_decimal(mean(gamma_025$CCT_includeXsquare), 20) # 0.00034450325588407350
specify_decimal(median(gamma_015$SMAT), 20) # 0.00247922534895639313
specify_decimal(median(gamma_025$SMAT), 20) # 0.00247922534895639313
gamma_025 <-
full_df %>%
filter(Npheno == 12,
delta == 1,
delta_select == 0.75,
gamma == 0.25)
sum(gamma_025$SMAT <= 0.05/50000) # 13
specify_decimal(median(gamma_025$SMAT), 20) # 0.00247922534895639313
specify_decimal(median(gamma_025$CCT), 20) # 0.00001122445
specify_decimal(median(gamma_025$CCT_includeXsquare), 20) # 0.0000008520913
gamma_015 <-
full_df %>%
filter(Npheno == 12,
delta == 1,
delta_select == 0.75,
gamma == 0.15)
sum(gamma_015$SMAT <= 0.05/50000) # 13
specify_decimal(mean(gamma_015$SMAT), 20) # 0.02245105569822626254
specify_decimal(mean(gamma_015$CCT), 20) # 0.00017748158796399526
specify_decimal(mean(gamma_015$CCT_includeXsquare), 20) # 7.927125e-05
specify_decimal(median(gamma_015$SMAT), 20) # 0.00275967613626793007
specify_decimal(median(gamma_015$CCT), 20) # 0.00001122445
specify_decimal(median(gamma_015$CCT_includeXsquare), 20) # 0.0000008520913
specify_decimal(max(gamma_015$SMAT), 20) # 0.48949447667456835731
specify_decimal(max(gamma_015$CCT), 20) # 0.02737312842337480401
specify_decimal(max(gamma_015$CCT_includeXsquare), 20) # 0.07169513212008116199
gamma_025 <-
full_df %>%
filter(Npheno == 12,
delta == 1,
delta_select == 0.75,
gamma == 0.25)
sum(gamma_025$SMAT <= 0.05/50000) # 13
specify_decimal(mean(gamma_025$SMAT), 20) # 0.02245105569822614111
specify_decimal(mean(gamma_025$CCT), 20) # 0.00017748158796399694
specify_decimal(mean(gamma_025$CCT_includeXsquare), 20) # 7.927125e-05
specify_decimal(median(gamma_025$SMAT), 20) # 0.00275967613626804109
specify_decimal(median(gamma_025$CCT), 20) # 4.826216e-06
specify_decimal(median(gamma_025$CCT_includeXsquare), 20) # 2.721883e-07
specify_decimal(max(gamma_025$SMAT), 20) # 0.48949447667455991962
specify_decimal(max(gamma_025$CCT), 20) # 0.02737312842337469299
specify_decimal(max(gamma_025$CCT_includeXsquare), 20) # 0.07169513212008526981
specify_decimal(min(gamma_025$SMAT), 20) # 5.690977e-09
specify_decimal(min(gamma_025$CCT), 20) # 3.183187e-11
specify_decimal(min(gamma_025$CCT_includeXsquare), 20) # 4.4409e-16
######### Phenotype is 12
gamma_015 <-
full_df %>%
filter(Npheno == 12,
delta == 1,
delta_select == 0.75,
gamma == 0.15)
sum(gamma_015$SMAT <= 0.05/50000) # 13
specify_decimal(mean(gamma_015$SMAT), 20) # 0.02245105569822626254
specify_decimal(mean(gamma_015$CCT), 20) # 0.00017748158796399526
specify_decimal(mean(gamma_015$CCT_includeXsquare), 20) # 7.927125e-05
specify_decimal(median(gamma_015$SMAT), 20) # 0.00275967613626793007
specify_decimal(median(gamma_015$CCT), 20) # 0.00001122445
specify_decimal(median(gamma_015$CCT_includeXsquare), 20) # 0.0000008520913
specify_decimal(max(gamma_015$SMAT), 20) # 0.78691592406092625289
specify_decimal(max(gamma_015$CCT), 20) # 0.02158895824613304981
specify_decimal(max(gamma_015$CCT_includeXsquare), 20) # 0.00913191681141212186
specify_decimal(min(gamma_015$SMAT), 20) # 5.690977e-09
pecify_decimal(min(gamma_015$CCT), 20) # 3.183187e-11
s
specify_decimal(min(gamma_015$CCT), 20) # 3.183187e-11
specify_decimal(min(gamma_015$CCT_includeXsquare), 20) # 4.4409e-16
gamma_035 <-
full_df %>%
filter(Npheno == 12,
delta == 1,
delta_select == 0.75,
gamma == 0.35)
sum(gamma_035$SMAT <= 0.05/50000) # 7
specify_decimal(mean(gamma_035$SMAT), 20) # 0.01343130059667275999
specify_decimal(mean(gamma_035$CCT), 20) # 0.00043311829323283712
specify_decimal(mean(gamma_035$CCT_includeXsquare), 20) # 0.00034450325588423938
specify_decimal(median(gamma_035$SMAT), 20) # 0.00247922534895639313
specify_decimal(median(gamma_035$CCT), 20) # 0.00001122445
specify_decimal(median(gamma_035$CCT_includeXsquare), 20) # 0.0000008520913
specify_decimal(median(gamma_035$CCT), 20) # 0.00001122445
specify_decimal(median(gamma_035$CCT_includeXsquare), 20) # 0.0000008520913
specify_decimal(max(gamma_035$SMAT), 20) # 0.48949447667456946753
specify_decimal(max(gamma_035$CCT), 20) # 0.02737312842337469299
specify_decimal(max(gamma_035$CCT_includeXsquare), 20) # 0.07169513212008515879
specify_decimal(min(gamma_035$SMAT), 20) # 5.690977e-09
specify_decimal(min(gamma_035$CCT), 20) # 3.183187e-11
specify_decimal(min(gamma_035$CCT_includeXsquare), 20) # 4.4409e-16
mean(gamma_035$CCT_includeXsquare)==mean(gamma_015$CCT_includeXsquare)
specify_decimal(mean(gamma_035$CCT_includeXsquare), 30) # 7.927125e-05
mean(gamma_025$CCT_includeXsquare)
mean(gamma_025$CCT_includeXsquare)==mean(gamma_035$CCT_includeXsquare)
median(gamma_035$SMAT)==median(gamma_025$SMAT)
median(gamma_035$SMAT)==median(gamma_015$SMAT)
median(gamma_035$SMAT)==median(gamma_025$SMAT)
gamma_035[which.min(gamma_035$SMAT),]
gamma_025[which.min(gamma_025$SMAT),]
gamma_015[which.min(gamma_015$SMAT),]
head(gamma_015)
gamma_015[which.max(gamma_015$SMAT),]
gamma_025[which.max(gamma_025$SMAT),]