diff clsi_profile.py @ 0:62226cd1acb5 draft

"planemo upload for repository https://github.com/rakesh4osdd/clsi_profile/tree/master commit ae6f2bc197b28000c56f6368ad044b350bc34f6a"

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/clsi_profile.py	Fri Jun 11 12:36:25 2021 +0000
@@ -0,0 +1,305 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[206]:
+
+
+# ASIST module2 | map AST result to the CLSI breakporints with combination antibiotics
+# By [e-mail], 06-Jun-2021
+import pandas as pd
+import re
+import sys
+
+
+# In[207]:
+
+
+#print(pd.__version__, re.__version__)
+
+
+# In[208]:
+
+
+# compare two MIC value strings
+def check_mic(mic1,mic2,mic_type):
+    #print(mic1,mic2,mic_type)
+    try:
+        if '/' in mic1:
+            m1a = mic1.split('/')[0]
+            m1b = mic1.split('/')[1]
+            if float(m1a)==0 or float(m1b)==0:
+                strain_type='Strain could not be classified'
+                return(strain_type)          
+        elif '/' in mic2:
+            m1a = mic1
+            if float(m1a)==0:
+                strain_type='Strain could not be classified'
+                return(strain_type)            
+            m1b = '1'
+        elif float(mic1)==0:
+            strain_type='Strain could not be classified'
+            return(strain_type)
+        else:
+            m1a = mic1
+            
+        if '-' in mic2:
+            m2a = mic2.split('-')[0]
+            m2b = mic2.split('-')[1]           
+         
+    except ValueError:
+        strain_type='Strain could not be classified' 
+        return(strain_type)
+    try:
+        if '-' in mic2 and mic_type == 'i':   # for intermediate only
+            if '/' in mic2:
+                m2a = mic2.split('-')[0].split('/')[0]
+                m2b = mic2.split('-')[0].split('/')[1]
+                m2aa = mic2.split('-')[1].split('/')[0]
+                m2bb = mic2.split('-')[1].split('/')[1]
+                if (float(m2aa)>=float(m1a)>=float(m2a) and float(m2bb)>=float(m1b)>=float(m2b)):
+                    #print('intermediate')
+                    m_type='Intermediate'
+                else:
+                    #print('not define')
+                    m_type='Strain could not be classified'
+            else:
+                m2a = mic2.split('-')[0]
+                m2b = mic2.split('-')[1] 
+                if (float(m2b)>=float(m1a)>=float(m2a)):
+                    #print('intermediate')
+                    m_type='Intermediate'
+                else:
+                    #print('not define')
+                    m_type='Strain could not be classified'                
+            #print (m1a,m1b,m2a,m2b,m2aa,m2bb)
+        elif '/' in mic2:
+            m2a = mic2.split('/')[0]
+            m2b = mic2.split('/')[1]
+            #print(m1a,m1b,m2a,m2b,mic_type)
+            if (mic_type=='s' and (float(m1a)<=float(m2a) and float(m1b)<=float(m2b))):
+                m_type='Susceptible'
+            elif (mic_type=='r' and (float(m1a)>=float(m2a) and float(m1b)>=float(m2b))):
+                m_type='Resistant'
+            elif (mic_type=='i' and (float(m1a)==float(m2a) and float(m1b)==float(m2b))):
+                m_type='Intermediate'
+            else:
+                m_type='Strain could not be classified'
+        elif '-' in mic2:
+                m_type='Strain could not be classified'
+        else:
+            m2a=mic2
+            if (mic_type=='s' and (float(m1a)<=float(m2a))):
+                m_type='Susceptible'
+            elif (mic_type=='r' and (float(m1a)>=float(m2a))):
+                m_type='Resistant'
+            elif (mic_type=='i' and (float(m1a)==float(m2a))):
+                m_type='Intermediate'
+            else:
+                m_type='Strain could not be classified-1'        
+    except IndexError:
+        strain_type='Strain could not be classified-2' 
+        return(strain_type)
+    
+    return(m_type)
+
+#check_mic('65','32-64','i')
+
+
+# In[209]:
+
+
+# compare MIC value in pandas list
+def sus_res_int(mic):
+    #print(mic)
+    o_mic = mic[0].replace(' ', '')
+    s_mic = mic[1].replace(' ', '')
+    r_mic = mic[2].replace(' ', '')
+    i_mic = mic[3].replace(' ', '')
+    try:
+        if check_mic(o_mic,s_mic,'s')=='Susceptible':
+            strain_type='Susceptible'
+        elif check_mic(o_mic,r_mic,'r')=='Resistant':
+            strain_type='Resistant'
+        elif check_mic(o_mic,i_mic,'i')=='Intermediate':
+            strain_type='Intermediate'                    
+        else:
+            strain_type='Strain could not be classified'
+    except ValueError:
+        strain_type='Strain could not be classified'            
+    return(strain_type)
+
+#mic=['128','16/4','128/4','32/4-64/4']
+#sus_res_int(mic)
+
+
+# In[210]:
+
+
+# for input argument
+input_user = sys.argv[1]
+input_clsi = sys.argv[2]
+output_table = sys.argv[3]
+
+
+# In[211]:
+
+"""
+input_user='input.csv'
+input_clsi='clsi.csv'
+output_profile=input_user+'_profile.csv'
+output_table=input_user+'_table.csv'
+"""
+
+# In[212]:
+
+
+# read user AST data with selected 3 columns
+strain_mic=pd.read_csv(input_user, sep=',', usecols =['Strain name', 'Antibiotics', 'MIC'],na_filter=False)
+
+
+# In[213]:
+
+
+clsi_bp=pd.read_csv(input_clsi,sep=',')
+
+
+# In[214]:
+
+
+#clsi_bp
+#strain_mic
+
+
+# In[215]:
+
+
+# convert MIC to numbers sMIC, rMIC
+clsi_bp['s_mic'] =clsi_bp[['Susceptible']].applymap(lambda x: (re.sub(r'[^0-9.\/-]', '', x)))
+clsi_bp['r_mic'] =clsi_bp[['Resistant']].applymap(lambda x: (re.sub(r'[^0-9.\/-]', '', x)))
+clsi_bp['i_mic'] = clsi_bp[['Intermediate']].applymap(lambda x: (re.sub(r'[^0-9.\/-]', '', x)))
+
+
+# In[216]:
+
+
+#clsi_bp['i_mic'] = clsi_bp[['Intermediate']].applymap(lambda x: (re.sub(r'[^0-9.\/-]', '', x)))
+
+
+# In[217]:
+
+
+# Read only numbers in MIC values
+#try:
+strain_mic['o_mic']=strain_mic[['MIC']].applymap(lambda x: (re.sub(r'[^0-9.\/]','', x)))
+#except TypeError:
+#    print('Waring: Error in MIC value')
+
+
+# In[218]:
+
+
+#strain_mic
+
+
+# In[219]:
+
+
+# capitalize each Antibiotic Name for comparision with removing whitespace
+strain_mic['Antibiotics']=strain_mic['Antibiotics'].str.capitalize().str.replace(" ","")
+clsi_bp['Antibiotics']=clsi_bp['Antibiotics'].str.capitalize().str.replace(" ","")
+
+
+# In[220]:
+
+
+#compare CLSI Antibiotics only
+#result=pd.merge(strain_mic, clsi_bp, on='Antibiotics',how='inner',  indicator=True)[['Strain name','Antibiotics', 'MIC', 'o_mic', 's_mic', 'r_mic','_merge']]
+try:
+    result=pd.merge(strain_mic, clsi_bp, on='Antibiotics',how='inner')[['Strain name','Antibiotics', 'MIC', 'o_mic', 's_mic', 'r_mic','i_mic']]
+except KeyError:
+    print('Waring: Error in input Values')
+
+
+# In[221]:
+
+
+#compare MIC values and assign Susceptible and Resistant to Strain
+#try:
+result[['CLSI_profile']] = result[['o_mic','s_mic','r_mic','i_mic']].apply(sus_res_int,axis = 1)
+#except ValueError:
+#    print('Waring: Error in input MIC value')
+
+
+# In[222]:
+
+
+#result
+
+
+# In[223]:
+
+
+#result[['Strain name', 'Antibiotics', 'MIC','s_mic','r_mic','CLSI_profile']].to_csv(output_profile,sep=',', index=False, encoding='utf-8-sig')
+
+
+# In[224]:
+
+
+#create a pivot table for ASIST
+table=result[['Strain name', 'Antibiotics','CLSI_profile']].drop_duplicates()
+result_table=pd.pivot_table(table, values ='CLSI_profile', index =['Strain name'],columns =['Antibiotics'], aggfunc = lambda x: ' '.join(x))
+
+
+# In[225]:
+
+
+#result_table
+
+
+# In[226]:
+
+
+#result_table.to_csv(output_table,na_rep='NA')
+
+
+# In[227]:
+
+
+# reorder the Antibiotics for ASIST
+clsi_ab=['Amikacin','Tobramycin','Gentamycin','Imipenem','Meropenem','Doripenem','Ciprofloxacin','Levofloxacin',
+         'Piperacillin/tazobactam','Ticarcillin/clavulanicacid','Cefotaxime','Ceftriaxone','Ceftazidime','Cefepime',
+         'Trimethoprim/sulfamethoxazole','Ampicillin/sulbactam','Colistin','Polymyxinb','Tetracycline','Doxicycline ',
+         'Minocycline']
+result_selected=result_table.filter(clsi_ab)
+
+
+# In[228]:
+
+
+#print(result_selected.shape, result_table.shape)
+
+
+# In[229]:
+
+
+result_selected.insert(0,'Resistance_phenotype','')
+
+
+# In[230]:
+
+
+#rename headers
+result_selected=result_selected.rename(columns = {'Ticarcillin/clavulanicacid':'Ticarcillin/clavulanic acid','Piperacillin/tazobactam':'Piperacillin/ tazobactam','Trimethoprim/sulfamethoxazole': 'Trimethoprim/ sulfamethoxazole','Ampicillin/sulbactam':'Ampicillin/ sulbactam', 'Polymyxinb': 'Polymyxin B'} )
+
+
+# In[231]:
+
+
+#result_selected
+
+
+# In[232]:
+
+
+result_selected.to_csv(output_table,na_rep='NA')
+