update src file

src/counts_matrix_generator.R

+############################# PCKGE REQUIRED ##############################
+library(DESeq2)
+library(ggplot2)
+library(tydiverse)
+### maybe others ###
+
+
 # fix seed
 set.seed(123)
 
@@ -6,50 +13,17 @@ set.seed(123)
 source("mydatalocal/counts_simulation/src/simulators.R")
 
 
-# visualization functions
-mu_effect_visualization <- function(mu_effect_res){
-  label_wrap <- c("mu observed", "N gene DE", "min(|logFC|)", "var observed")
-  names(label_wrap) <- c("mu_observ", "res_DEA", "statistical_power", "var_observ")
-  figure = mu_effect_res %>% ggplot(., aes(x=vec_of_mu, y = value, col=factor(N_rep))) +
-     geom_point() + facet_wrap(~variable, scales = "free_y", labeller = labeller(variable = label_wrap))  + labs(color = "N replicates")
-  return(figure)
-}
-
-size_effect_visualization <- function(alpha_effect_res){
-  label_wrap <- c("mu observed", "N gene DE", "min(|logFC|)", "var observed")
-  names(label_wrap) <- c("mu_observ", "res_DEA", "statistical_power", "var_observ")
-  figure = alpha_effect_res %>% ggplot(., aes(x=vec_of_alpha, y = value, col=factor(N_rep))) +
-    geom_point() + facet_wrap(~variable, scales = "free_y", labeller = labeller(variable = label_wrap))  + labs(color = "N replicates")
-  return(figure)
-}
+#visualization function
+source("mydatalocal/counts_simulation/src/visualization_fun.R")
 
 
-## main
-# Params to specify design
-min_rep = 2 #/!\  = 1 forbidden
-max_rep = 10
+########################## INPUT PARAMS #####################################
 N_cond = 2
 N_gene = 6000
+n_rep_sim = seq(2, 5, by = 1) ### number of replicate to assessed
 
 
-mu_simul = seq(100, 15000, by = 200)
-mu_simul
-mu_simul <- rep.int(1500, 8)
-res_simul <- mu_effect(alpha = 2.9, mu_simul)
-reshape_res_simul <- res_simul %>% reshape2::melt(.,id = c("vec_of_mu"))
-mu_effect_visualization(reshape_res_simul)
-
-
-alpha_simul = seq(0.01, 10, by = 0.1)
-alpha_simul
-res_simul2 <- size_effect(mu = 10000, alpha_simul)
-res_simul2
-reshape_res_simul2 <- res_simul2 %>% reshape2::melt(.,id = c("vec_of_alpha"))
-size_effect_visualization(reshape_res_simul2)
-
-
-## replicate effect
-n_rep_sim = seq(2, 5, by = 1)
+############################ MU effect  #######################################
 
 mu_simul_dtf_res <- data.frame()
 for (N_rep in n_rep_sim){
@@ -62,16 +36,17 @@ for (N_rep in n_rep_sim){
   mu_simul_dtf_res <- rbind(mu_simul_dtf_res, tmp_reshape_res_simul)
 }
 
-## LOG transform
+######  LOG transform  #######
+
+# -> SEE linearity of var observed & mu
+
 #mu_simul_dtf_res$value[mu_simul_dtf_res$variable=="var_observ"]<-log(mu_simul_dtf_res$value[mu_simul_dtf_res$variable=="var_observ"])
 #mu_simul_dtf_res$vec_of_mu <- log(mu_simul_dtf_res$vec_of_mu)
 
-## Visualization
+###### Visualization ######
 figure_mu_effect <- mu_effect_visualization(mu_simul_dtf_res)
 figure_mu_effect
-svg("mydatalocal/counts_simulation/img/fig_mu_effect.svg")
-figure_mu_effect
-dev.off()
+
 
 ########################### ALPHA effect ####################################
 n_rep_sim = seq(2, 5, by = 1)
@@ -86,10 +61,47 @@ for (N_rep in n_rep_sim){
   tmp_reshape_res_simul <- res_simul %>% reshape2::melt(.,id = c("vec_of_alpha", "N_rep"))
   alpha_simul_dtf_res <- rbind(alpha_simul_dtf_res, tmp_reshape_res_simul)
 }
+
+
+###### Visualization ######
 alpha_simul_dtf_res
 figure_alpha_effect <- size_effect_visualization(alpha_simul_dtf_res)
+figure_alpha_effect
+
+
+
+########################### EXPORT RESULTS #################################
+
+svg("mydatalocal/counts_simulation/img/fig_mu_effect.svg")
+figure_mu_effect
+dev.off()
 
 svg("mydatalocal/counts_simulation/img/fig_size_effect.svg")
 figure_alpha_effect
 dev.off()
 
+
+
+########################### Beta test  #####################################
+
+## main
+# Params to specify design
+min_rep = 2 #/!\  = 1 forbidden
+max_rep = 10
+
+
+
+mu_simul = seq(100, 15000, by = 200)
+mu_simul
+mu_simul <- rep.int(1500, 8)
+res_simul <- mu_effect(alpha = 2.9, mu_simul)
+reshape_res_simul <- res_simul %>% reshape2::melt(.,id = c("vec_of_mu"))
+mu_effect_visualization(reshape_res_simul)
+
+
+alpha_simul = seq(0.01, 10, by = 0.1)
+alpha_simul
+res_simul2 <- size_effect(mu = 10000, alpha_simul)
+res_simul2
+reshape_res_simul2 <- res_simul2 %>% reshape2::melt(.,id = c("vec_of_alpha"))
+size_effect_visualization(reshape_res_simul2)