diff --git a/README.md b/README.md
index f8c05f3f19d1878fff2ac0ed69733e562b95a19b..2d69f7b6e3ad4a76b3055931ce826db96f68f983 100644
--- a/README.md
+++ b/README.md
@@ -1,24 +1,10 @@
-Workflow for generating phenotype score combinations and correlating them to biofilm. 
+
 
 There is one rule: no Excel. Every time I use excel, I have to rename the file and they get lost and I can't retrace my steps. Forcing no excel, I can see every step and fix them where I need to. 
 
 First things first: 
-
-1. Generate normalized scores from the sorted scores. 
-	* A sorted score is a the average of the raw scores from the biological replicates. An individual photo is a biological replicate. 
-
-	* `score_wrangler.R` takes in the un-normalized scores and generates a normalized column using the `preProcess()` function from the `caret` package. 
-	
-	* This program will also remove data that we do not want (we removed certain non-albicans *Candida* species that didn't grow under certain conditions. 
-
-	* After this, the files are modified with `column_clean.py` (called inside the R script) to remove the leading column and to clean up the column content if necessary. 
-
-	* Finally, the program makes a file with all the score data in it. Repeatability. No Excel. 
-
-	* I also had it combine all the scores. That just made things a lot easier. 
-
 	
-2. Correlate all the normalized sum scores with biofilm.  
+1. Correlate all the normalized sum scores with biofilm.  
 	* I need a table for these that include the information on what scores are included in the composite scores, the media, and the temperature, as well as the correlation metrics. 
 
 	* `additive_correlator.R` Using the `cor.test()` function described by [STHDA](http://www.sthda.com/english/wiki/correlation-test-between-two-variables-in-r)
diff --git a/column_clean.py b/column_clean.py
deleted file mode 100644
index 2a5f47b366ee384d658ab67a44d65c2ea4148f26..0000000000000000000000000000000000000000
--- a/column_clean.py
+++ /dev/null
@@ -1,45 +0,0 @@
-import sys
-
-file_name = sys.argv[1]
-
-file = open( file_name, "r" )
-
-biofilm = 0
-if "biofilm" in file_name: 
-	biofilm = 1
-
-# Gross header : MAY.Strain..	Species	Soll.Clade	Isolation.Site	MTL.Genotype	Media	Temperature..C.	MJD.Phenotype.Score	MJD.Score.St..Dev.	RJF.Phenotype.Score	RJF.Score.St..Dev.	Total.Average.Phenotype.Score	Total.Phenotype.Score.St..Dev.	Normalized.Scores	
-new_header = "May Strain, Species, Soll Clade, Isolation Site, MTL Genotype, Media, Temperature ("+ u"\N{DEGREE SIGN}" + "C), MJD Phenotype Score, 	MJD Score St. Dev., RJF Phenotype Score, RJF Score St. Dev., Total Average Phenotype Score, Total Phenotype Score St. Dev., Normalized Scores"
-biofilm_header = "May Strain, Species, Soll Clade, Isolation Site, Media, Temperature ("+ u"\N{DEGREE SIGN}" + "C), Total Average Phenotype Score, Total Phenotype Score St. Dev., Normalized Scores"
-
-new_file = open( "nc_" + file_name[5:],"w") #nc = normalized clean
-
-header = 1
-for lines in file: 
-
-	if header:
-
-		if biofilm: 
-			print( biofilm_header, file = new_file )
-		else: 
-			print( new_header, file = new_file )
-
-		file_header = lines.split(",")
-		header = 0
-		continue
-
-	line_list = lines.split(",")
-	
-	if biofilm: 
-		new_line_list = line_list[0:]
-	else:
-		new_line_list = line_list[0:]
-		# new_line_list = line_list[1:7] # Include these two lines if you want to remove the per-person scoring
-		# new_line_list.extend( line_list[11:] )
-
-	line_str = ",".join(new_line_list).strip()
-
-	print( line_str, file = new_file )
-
-file.close()
-new_file.close()
diff --git a/score_wrangler.py b/score_wrangler.py
deleted file mode 100644
index 49e9103b8e9c6fd459b4c688734453351dd55882..0000000000000000000000000000000000000000
--- a/score_wrangler.py
+++ /dev/null
@@ -1,10 +0,0 @@
-adh_file = open( "adhesion_scores_sorted.csv", "r" )
-fil_file = open( "filamentation_scores_sorted.csv", "r")
-inv_file = open( "invasion_scores_sorted.csv","r" )
-
-
-
-
-adh_file.close()
-fil_file.close()
-inv_file.close()
\ No newline at end of file