Updated comments for readability

src/penalty_selection.py

@@ -9,9 +9,10 @@
 
 #------------------------------------------------------------#
 # The automated lambda selection pipeline is as follows: 
-# 1) Run CliP with 11 different lambda: [0.01, 0.03, 0.05, 0.075, 0.1, 0.125, 0.15, 0.175, 0.2, 0.225, 0.25]. 
+# 1) Run CliP with 11 different lambdas: [0.01, 0.03, 0.05, 0.075, 0.1, 0.125, 0.15, 0.175, 0.2, 0.225, 0.25]. 
 # 2) For each sample, compute a score: A = |(max(CP)−purity)/purity|. 
 # If there are one or more results that satisfy A < 0.01, we select the largest lambda associated with those results. 
+# (We observed A<0.01 in more than 70% of the PCAWG samples)
 # If all scores A are greater than 0.01, we choose the lambda associated with the smallest A.
 #------------------------------------------------------------#
 

src/postprocess.R

@@ -39,6 +39,7 @@ least.ratio         <- 0.05
 SAFETY              <- 0.05
 N.REP               <- 30
 RATIO.TH            <- 0.90
+# The 11 lambda values in the default lambda list
 Lambda_list = c(0.01, 0.03, 0.05, 0.075, 0.1, 0.125, 0.15, 0.175, 0.2, 0.225, 0.25)
 
 if(!dir.exists(output.prefix)){