diff --git a/ks_test_all_timepoints.R b/ks_test_all_timepoints.R
new file mode 100644
index 0000000..a1a0936
--- /dev/null
+++ b/ks_test_all_timepoints.R
@@ -0,0 +1,108 @@
+#!/usr/bin/Rscript   
+getwd()
+setwd('~/git/covid_analysis/')
+getwd()
+############################################################
+# TASK: basic plots
+
+# useful links:
+# http://www.sthda.com/english/wiki/ggplot2-dot-plot-quick-start-guide-r-software-and-data-visualization
+############################################################
+# source data
+source("read_data.R")
+############################################################
+#===================================
+# output: KS test for cumulated time
+#===================================
+ks_all_timepoints = paste0(outdir_stats, "KS_test_all_timepoints_v3.csv")
+
+############################################################
+# data assignment for stats
+wf = wf_data
+lf = lf_data
+#========================================================
+# data assignment for stats
+lf
+sum(is.na(lf$value))
+
+#lf = lf[!is.na(lf$value),]
+#sum(is.na(lf$value))
+#str(lf$value)
+
+#========================================================
+# ks test to analyse dist (all timepoints)
+table(lf$outcomes, lf$mediator)
+str(lf$outcomes)
+
+table(lf$outcomes); str(lf$outcomes)
+
+lf_death = lf[lf$outcomes==0,]
+lf_recovered = lf[lf$outcomes==1,]
+
+#=======================================================================
+# for one
+ks_pf = ks.test(lf_death$value[lf_death$mediator == "PF"]
+                ,  lf_recovered$value[lf_recovered$mediator == "PF"]); ks_pf
+
+ks_srage = ks.test(lf_death$value[lf_death$mediator == "sRAGE"]
+                ,  lf_recovered$value[lf_recovered$mediator == "sRAGE"]); ks_srage
+
+#=======================================================================
+# loop
+ks_df = data.frame()
+mediator_names = levels(factor(lf$mediator))
+
+for (i in mediator_names) {
+  df = data.frame(mediator = NA, test_name = NA, ks_statistic = NA, ks_pvalue = NA)
+  #df = data.frame()
+  
+  #print(i)
+  ks.test(lf_death$value[lf_death$mediator == i]
+                ,  lf_recovered$value[lf_recovered$mediator == i])
+  
+  med = i
+  ks_method = ks.test(lf_death$value[lf_death$mediator == i]
+                      ,  lf_recovered$value[lf_recovered$mediator == i])$method
+  
+  ks_statistic = ks.test(lf_death$value[lf_death$mediator == i]
+               ,  lf_recovered$value[lf_recovered$mediator == i])$statistic
+  
+  ks_pval = ks.test(lf_death$value[lf_death$mediator == i]
+                         ,  lf_recovered$value[lf_recovered$mediator == i])$p.value
+  
+  #print(c(med, ks_method, ks_statistic[[1]], ks_pval))
+  
+  df$mediator = med
+  df$test_name = ks_method 
+  df$ks_statistic = ks_statistic[[1]]
+  df$ks_pvalue = ks_pval
+  
+  print(df)
+  ks_df = rbind(ks_df, df)
+}
+
+#=======================================================================
+# formatting
+#=======================================================================
+ks_df$group = "0 vs 1"
+ks_df$timepoint = "t1,t2,t3"
+
+str(ks_df)
+ks_df$pvalue_signif = ks_df$ks_pvalue
+str(ks_df$pvalue_signif)
+
+# adding pvalue_signif
+ks_df = dplyr::mutate(ks_df,pvalue_signif = case_when(pvalue_signif == 0.05 ~ "."
+                                    , pvalue_signif <=0.0001 ~ '****'
+                                    , pvalue_signif <=0.001 ~ '***'
+                                    , pvalue_signif <=0.01 ~ '**'
+                                    , pvalue_signif <0.05 ~ '*'
+                                    , TRUE ~ 'ns'))
+
+
+#******************
+# write output file: KS test
+#******************
+cat("Output of KS test all timeoints by group will be in:", ks_all_timepoints)
+write.csv(ks_df, ks_all_timepoints, row.names = FALSE)
+
diff --git a/ks_test_time.R b/ks_test_time.R
new file mode 100644
index 0000000..4df3778
--- /dev/null
+++ b/ks_test_time.R
@@ -0,0 +1,260 @@
+#!/usr/bin/Rscript   
+getwd()
+setwd('~/git/covid_analysis/')
+getwd()
+############################################################
+# TASK: basic plots
+
+# useful links:
+# http://www.sthda.com/english/wiki/ggplot2-dot-plot-quick-start-guide-r-software-and-data-visualization
+############################################################
+# source data
+source("read_data.R")
+############################################################
+#===================================
+# output: KS test at each timepoint
+#===================================
+ks_each_time = paste0(outdir_stats, "KS_test_by_time_v3.csv")
+
+############################################################
+# data assignment for stats
+wf = wf_data
+lf = lf_data
+#========================================================
+sum(is.na(lf$value))
+lf$log10_value = log10(lf$value)
+
+#lf = lf[!is.na(lf$value),]
+#sum(is.na(lf$value))
+#str(lf$value)
+
+########################################################################
+#==============
+# timepoint: t1
+#==============
+lf_t1 = lf[lf$timepoint=="t1",]
+
+table(lf_t1$outcomes)
+
+lf_death_t1 = lf_t1[lf_t1$outcomes == 0,]
+lf_recovered_t1 = lf_t1[lf_t1$outcomes == 1,]
+
+#=======================================================================
+# individual mediator: t1
+ks.test(lf_death_t1$value[lf_death_t1$mediator == "PF"]
+, lf_recovered_t1$value[lf_recovered_t1$mediator == "PF"])
+
+ks.test(lf_death_t1$value[lf_death_t1$mediator == "sRAGE"]
+        , lf_recovered_t1$value[lf_recovered_t1$mediator == "sRAGE"])
+
+#=======================================================================
+# loop: t1
+ks_df_t1 = data.frame()
+mediator_names = levels(factor(lf$mediator))
+
+for (i in mediator_names) {
+  df_t1 = data.frame(mediator = NA, test_name = NA, ks_statistic = NA, ks_pvalue = NA)
+  #print(i)
+  ks.test(lf_death_t1$value[lf_death_t1$mediator == i]
+          ,  lf_recovered_t1$value[lf_recovered_t1$mediator == i])
+  
+  med = i
+  ks_method = ks.test(lf_death_t1$value[lf_death_t1$mediator == i]
+                      ,  lf_recovered_t1$value[lf_recovered_t1$mediator == i])$method
+  
+  ks_statistic = ks.test(lf_death_t1$value[lf_death_t1$mediator == i]
+                         ,  lf_recovered_t1$value[lf_recovered_t1$mediator == i])$statistic
+  
+  ks_pval = ks.test(lf_death_t1$value[lf_death_t1$mediator == i]
+                    ,  lf_recovered_t1$value[lf_recovered_t1$mediator == i])$p.value
+  
+  #print(c(med, ks_method, ks_statistic[[1]], ks_pval))
+  
+  df_t1$mediator = med
+  df_t1$test_name = ks_method 
+  df_t1$ks_statistic = ks_statistic[[1]]
+  df_t1$ks_pvalue = ks_pval
+  
+  print(df)
+  ks_df_t1 = rbind(ks_df_t1, df_t1)
+}
+
+# formatting
+ks_df_t1$group = "0 vs 1"
+ks_df_t1$timepoint = "t1"
+
+str(ks_df_t1)
+ks_df_t1$pvalue_signif = ks_df_t1$ks_pvalue
+str(ks_df_t1$pvalue_signif)
+
+ks_df_t1 = dplyr::mutate(ks_df_t1
+                         , pvalue_signif = case_when(pvalue_signif == 0.05 ~ "."
+                                                     , pvalue_signif <=0.0001 ~ '****'
+                                                     , pvalue_signif <=0.001 ~ '***'
+                                                     , pvalue_signif <=0.01 ~ '**'
+                                                     , pvalue_signif <0.05 ~ '*'
+                                                     , TRUE ~ 'ns'))
+
+##########################################################################
+#==============
+# timepoint: t2
+#==============
+lf_t2 = lf[lf$timepoint=="t2",]
+
+table(lf_t2$outcomes)
+
+lf_death_t2 = lf_t2[lf_t2$outcomes == 0,]
+lf_recovered_t2 = lf_t2[lf_t2$outcomes == 1,]
+#=======================================================================
+# individual mediator: t2
+ks.test(lf_death_t2$value[lf_death_t2$mediator == "PF"]
+        , lf_recovered_t2$value[lf_recovered_t2$mediator == "PF"])
+
+ks.test(lf_death_t2$value[lf_death_t2$mediator == "sRAGE"]
+        , lf_recovered_t2$value[lf_recovered_t2$mediator == "sRAGE"])
+
+#=======================================================================
+# loop: t2
+ks_df_t2 = data.frame()
+mediator_names = levels(factor(lf$mediator))
+
+for (i in mediator_names) {
+  df_t2 = data.frame(mediator = NA, test_name = NA, ks_statistic = NA, ks_pvalue = NA)
+  #print(i)
+  ks.test(lf_death_t2$value[lf_death_t2$mediator == i]
+          ,  lf_recovered_t2$value[lf_recovered_t2$mediator == i])
+  
+  med = i
+  ks_method = ks.test(lf_death_t2$value[lf_death_t2$mediator == i]
+                      ,  lf_recovered_t2$value[lf_recovered_t2$mediator == i])$method
+  
+  ks_statistic = ks.test(lf_death_t2$value[lf_death_t2$mediator == i]
+                         ,  lf_recovered_t2$value[lf_recovered_t2$mediator == i])$statistic
+  
+  ks_pval = ks.test(lf_death_t2$value[lf_death_t2$mediator == i]
+                    ,  lf_recovered_t2$value[lf_recovered_t2$mediator == i])$p.value
+  
+  #print(c(med, ks_method, ks_statistic[[1]], ks_pval))
+  
+  df_t2$mediator = med
+  df_t2$test_name = ks_method 
+  df_t2$ks_statistic = ks_statistic[[1]]
+  df_t2$ks_pvalue = ks_pval
+  
+  print(df)
+  ks_df_t2 = rbind(ks_df_t2, df_t2)
+}
+
+# formatting
+ks_df_t2$group = "0 vs 1"
+ks_df_t2$timepoint = "t2"
+
+str(ks_df_t2)
+ks_df_t2$pvalue_signif = ks_df_t2$ks_pvalue
+str(ks_df_t2$pvalue_signif)
+
+ks_df_t2 = dplyr::mutate(ks_df_t2
+                         , pvalue_signif = case_when(pvalue_signif == 0.05 ~ "."
+                                                     , pvalue_signif <=0.0001 ~ '****'
+                                                     , pvalue_signif <=0.001 ~ '***'
+                                                     , pvalue_signif <=0.01 ~ '**'
+                                                     , pvalue_signif <0.05 ~ '*'
+                                                     , TRUE ~ 'ns'))
+#=======================================================================
+#==============
+# timepoint: t3
+#==============
+lf_t3 = lf[lf$timepoint=="t3",]
+
+table(lf_t3$outcomes)
+
+lf_death_t3 = lf_t3[lf_t3$outcomes == 0,]
+lf_recovered_t3 = lf_t3[lf_t3$outcomes == 1,]
+#=======================================================================
+# individual mediator: t3
+ks.test(lf_death_t3$value[lf_death_t3$mediator == "PF"]
+        , lf_recovered_t3$value[lf_recovered_t3$mediator == "PF"])
+
+ks.test(lf_death_t3$value[lf_death_t3$mediator == "sRAGE"]
+        , lf_recovered_t3$value[lf_recovered_t3$mediator == "sRAGE"])
+
+#=======================================================================
+# loop: t3
+ks_df_t3 = data.frame()
+mediator_names = levels(factor(lf$mediator))
+
+for (i in mediator_names) {
+  df_t3 = data.frame(mediator = NA, test_name = NA, ks_statistic = NA, ks_pvalue = NA)
+  #print(i)
+  ks.test(lf_death_t3$value[lf_death_t3$mediator == i]
+          ,  lf_recovered_t3$value[lf_recovered_t3$mediator == i])
+  
+  med = i
+  ks_method = ks.test(lf_death_t3$value[lf_death_t3$mediator == i]
+                      ,  lf_recovered_t3$value[lf_recovered_t3$mediator == i])$method
+  
+  ks_statistic = ks.test(lf_death_t3$value[lf_death_t3$mediator == i]
+                         ,  lf_recovered_t3$value[lf_recovered_t3$mediator == i])$statistic
+  
+  ks_pval = ks.test(lf_death_t3$value[lf_death_t3$mediator == i]
+                    ,  lf_recovered_t3$value[lf_recovered_t3$mediator == i])$p.value
+  
+  #print(c(med, ks_method, ks_statistic[[1]], ks_pval))
+  
+  df_t3$mediator = med
+  df_t3$test_name = ks_method 
+  df_t3$ks_statistic = ks_statistic[[1]]
+  df_t3$ks_pvalue = ks_pval
+  
+  print(df)
+  ks_df_t3 = rbind(ks_df_t3, df_t3)
+}
+
+# formatting
+ks_df_t3$group = "0 vs 1"
+ks_df_t3$timepoint = "t3"
+
+str(ks_df_t3)
+ks_df_t3$pvalue_signif = ks_df_t3$ks_pvalue
+str(ks_df_t3$pvalue_signif)
+
+ks_df_t3 = dplyr::mutate(ks_df_t3
+                         , pvalue_signif = case_when(pvalue_signif == 0.05 ~ "."
+                                                     , pvalue_signif <=0.0001 ~ '****'
+                                                     , pvalue_signif <=0.001 ~ '***'
+                                                     , pvalue_signif <=0.01 ~ '**'
+                                                     , pvalue_signif <0.05 ~ '*'
+                                                     , TRUE ~ 'ns'))
+
+##########################################################################
+# combine all three ks_dfs
+n_dfs = 3
+if ( all.equal(nrow(ks_df_t1), nrow(ks_df_t2), nrow(ks_df_t3)) && 
+     all.equal(ncol(ks_df_t1), ncol(ks_df_t2), ncol(ks_df_t3)) ){
+  cat("\nPASS: Calculating expected rows and cols for sanity checks on combined_dfs")
+  expected_rows = nrow(ks_df_t1) * n_dfs
+  expected_cols = ncol(ks_df_t1)
+  ks_df_combined = rbind(ks_df_t1, ks_df_t2, ks_df_t3)
+ if ( nrow(ks_df_combined) == expected_rows && ncol(ks_df_combined) == expected_cols ){
+   cat("\nPASS: combined df successfully created"
+       , "\nnrow combined_df:", nrow(ks_df_combined)
+       , "\nncol combined_df:", ncol(ks_df_combined))
+   }
+  else{
+      cat("\nFAIL: Dim mismatch"
+        , "\nExpected rows:", expected_rows
+        , "\nGot:", nrow(ks_df_combined)
+        , "\nExpected cols:", expected_cols
+        , "\nGot:", ncol(ks_df_combined))
+        }
+  }else{
+  cat("\nFAIL: Could not generate expected_rows and/or expected_cols"
+      , "\nCheck hardcoded value of n_dfs")
+  }  
+
+#=======================================================================
+#******************
+# write output file: KS test
+#******************
+cat("Output of KS test by time will be in:", ks_each_time)
+write.csv(ks_df_combined, ks_each_time , row.names = FALSE)