# HG changeset patch # User rakesh4osdd # Date 1624944041 0 # Node ID 68329942257575cf0a6a672426fbd03e26347bce # Parent 306236ec05112b65262386daf78310a55ffdad4e "planemo upload for repository https://github.com/rakesh4osdd/asist/tree/master commit f085b88bf75f7b45ac3b0c4e1c39214c0ac0b67d" diff -r 306236ec0511 -r 683299422575 README.md --- a/README.md Fri Jun 11 13:20:08 2021 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,2 +0,0 @@ -# clsi_profile -CLSI profile for ASIST diff -r 306236ec0511 -r 683299422575 README.rst --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/README.rst Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,20 @@ +# clsi_profile + + CLSI profile for ASIST using the CLSI standards 2020 by AST profiling for bacteria. It help to generate the input file for ASIST program based on MIC values provided by CLSI based AST profiling. + +# ASIST: Antimicrobial Susceptibility standards** + + In the first column strain names will be mentioned, the second column will be left blank for getting resistance phenotype, starting two rows will comprise antibiotic names (first row) and antibiotic classes (second row). The data for the resistance profile will then start from the C3 column of an excel file which can be converted into a .csv file. Since B3 is left blank, after implementing the algorithm, column B3 will be filled with the resistance phenotype (susceptible, MDR, XDR, PDR). + +**Example Input CSV file:** + + Strain name,Resistance_phenotype,Antibiotic_A1,Antibiotic_A2,Antibiotic_A_N + Strain_1,Phenotype_1,Resistant,Resistant,Resistant + Strain_2,Phenotype_2,Resistant,Susceptible,Resistant + + Link to the code : https://github.com/rakesh4osdd/asist + + +# ASIST tool suite + + These tools can be install from Galaxy toolshed to a Galaxy installation https://galaxyproject.org/admin/get-galaxy/. diff -r 306236ec0511 -r 683299422575 asist_dynamic.ipynb --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/asist_dynamic.ipynb Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,310 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1309, + "id": "27cfc66f", + "metadata": {}, + "outputs": [], + "source": [ + "#ASIST program for phenotype based on Antibiotics profile\n", + "# create a profile based on selected antibiotics only\n", + "# rakesh4osdd@gmail.com, 14-June-2021" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "75a352b7", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import sys\n", + "import os\n", + "from collections import Counter" + ] + }, + { + "cell_type": "code", + "execution_count": 176, + "id": "d66ec0d2", + "metadata": {}, + "outputs": [], + "source": [ + "input_file=sys.argv[1]\n", + "output_file=sys.argv[2]\n", + "#input_file='test-data/asist_input.csv'\n", + "#output_file='test-data/asist_output.csv'" + ] + }, + { + "cell_type": "code", + "execution_count": 177, + "id": "bf24c946", + "metadata": {}, + "outputs": [], + "source": [ + "# strain_profile to phenotype condition\n", + "def s_phen(sus,res,intm,na,pb_sus):\n", + " if (sus>0 and res==0 and na>=0):\n", + " #print('Possible Susceptible')\n", + " phen='Possible Susceptible'\n", + " elif (sus>=0 and 3<=res<7 and na>=0 and pb_sus==0):\n", + " #print('Possible MDR')\n", + " phen='Possible MDR'\n", + " elif (sus>=0 and 7<=res<9 and na>=0 and pb_sus==0):\n", + " #print('Possible XDR')\n", + " phen='Possible XDR'\n", + " #special cases\n", + " elif (sus>=1 and res>0 and na>=0 and pb_sus==1):\n", + " #print('Possible XDR')\n", + " phen='Possible XDR'\n", + " #special cases\n", + " elif (sus>0 and res==9 and na>=0):\n", + " #print('Possible XDR')\n", + " phen='Possible XDR'\n", + " elif (sus==0 and res==9 and na>=0):\n", + " #print('Possible TDR')\n", + " phen='Possible TDR'\n", + " else:\n", + " #print('Strain could not be classified')\n", + " phen='Strain could not be classified ('+ str(intm)+' | ' + str(na) +')'\n", + " return(phen)\n", + "\n", + "#print(s_phen(1,9,0,0))" + ] + }, + { + "cell_type": "code", + "execution_count": 178, + "id": "8bad7d9d", + "metadata": {}, + "outputs": [], + "source": [ + "# define Antibiotic groups as per antibiotic of CLSI breakpoints MIC\n", + "#Aminoglycoside\n", + "cat1=['Amikacin','Tobramycin','Gentamycin','Netilmicin']\n", + "#Beta-lactams- Carbapenems\n", + "cat2=['Imipenem','Meropenam','Doripenem']\n", + "#Fluoroquinolone\n", + "cat3=['Ciprofloxacin','Levofloxacin']\n", + "#Beta-lactam inhibitor\n", + "cat4=['Piperacillin/tazobactam','Ticarcillin/clavulanicacid']\n", + "#Cephalosporin\n", + "cat5=['Cefotaxime','Ceftriaxone','Ceftazidime','Cefepime']\n", + "#Sulfonamides\n", + "cat6=['Trimethoprim/sulfamethoxazole']\n", + "#Penicillins/beta-lactamase\n", + "cat7=['Ampicillin/sulbactam']\n", + "#Polymyxins\n", + "cat8=['Colistin','Polymyxinb']\n", + "#Tetracycline\n", + "cat9=['Tetracycline','Doxicycline','Minocycline']\n", + "\n", + "def s_profiler(pd_series):\n", + " #print(type(pd_series),'\\n', pd_series)\n", + " #create a dictionary of dataframe series\n", + " cats={'s1':cat1,'s2':cat2,'s3':cat3,'s4':cat4,'s5':cat5,'s6':cat6,'s7':cat7,'s8':cat8,'s9':cat9}\n", + " # find the antibiotics name in input series\n", + " for cat in cats:\n", + " #print(cats[cat])\n", + " cats[cat]=pd_series.filter(cats[cat])\n", + " #print(cats[cat])\n", + " #define res,sus,intm,na,pb_sus\n", + " res=0\n", + " sus=0\n", + " intm=0\n", + " na=0\n", + " pb_sus=0\n", + " # special case of 'Polymyxin b' for its value\n", + " if 'Polymyxinb' in pd_series:\n", + " ctp=cats['s8']['Polymyxinb'].strip().lower()\n", + " if ctp == 'susceptible':\n", + " pb_sus=1\n", + " #print((ctp,p_sus))\n", + " # check all categories\n", + " for cat in cats:\n", + " #ctp=cats['s8'].iloc[i:i+1].stack().value_counts().to_dict()\n", + " #print(ctp)\n", + " # Pandas series\n", + " ct=cats[cat].value_counts().to_dict()\n", + " #print(ct)\n", + " # remove whitespace and convert to lowercase words\n", + " ct = {k.strip().lower(): v for k, v in ct.items()}\n", + " #print(ct)\n", + " k=Counter(ct)\n", + " #j=Counter(ct)+Counter(j)\n", + " #print(j)\n", + " # category wise marking\n", + " if k['resistant']>=1:\n", + " res=res+1\n", + " if k['susceptible']>=1:\n", + " sus=sus+1\n", + " if k['intermediate']>=1:\n", + " intm=intm+1\n", + " if k['na']>=1:\n", + " na=na+1\n", + " #print(sus,res,intm,na,pb_sus)\n", + " #print(s_phen(sus,res,intm,na,pb_sus))\n", + " return(s_phen(sus,res,intm,na,pb_sus))" + ] + }, + { + "cell_type": "code", + "execution_count": 179, + "id": "7629fc10", + "metadata": {}, + "outputs": [], + "source": [ + "#input_file='input2.csv_table.csv'\n", + "#output_file=input_file+'_output.txt'\n", + "strain_profile=pd.read_csv(input_file, sep=',',na_filter=False,skipinitialspace = True)" + ] + }, + { + "cell_type": "code", + "execution_count": 180, + "id": "bed1abba", + "metadata": {}, + "outputs": [], + "source": [ + "old_strain_name=strain_profile.columns[0]\n", + "new_strain_name=old_strain_name.capitalize().strip().replace(' ', '')" + ] + }, + { + "cell_type": "code", + "execution_count": 181, + "id": "a64b5022", + "metadata": {}, + "outputs": [], + "source": [ + "# make header capitalization, remove leading,lagging, and multiple whitespace for comparision\n", + "strain_profile.columns=strain_profile.columns.str.capitalize().str.strip().str.replace('\\s+', '', regex=True)\n", + "#print(strain_profile.columns)\n", + "#strain_profile.head()\n", + "#strain_profile.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "id": "caac57d7", + "metadata": {}, + "outputs": [], + "source": [ + "# add new column in dataframe on second position\n", + "strain_profile.insert(1, 'Strain phenotype','')\n", + "#strain_profile.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 183, + "id": "eb4b0c4d", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "strain_profile['Strain phenotype'] = strain_profile.apply(lambda x: (s_profiler(x)), axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 184, + "id": "86441c0f", + "metadata": {}, + "outputs": [], + "source": [ + "#strain_profile.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 185, + "id": "75698be5", + "metadata": {}, + "outputs": [], + "source": [ + "#rename headers for old name\n", + "strain_profile=strain_profile.rename(columns = {new_strain_name:old_strain_name, 'Ticarcillin/clavulanicacid':'Ticarcillin/ clavulanic acid','Piperacillin/tazobactam':'Piperacillin/ tazobactam','Trimethoprim/sulfamethoxazole': 'Trimethoprim/ sulfamethoxazole','Ampicillin/sulbactam':'Ampicillin/ sulbactam', 'Polymyxinb': 'Polymyxin B'} )" + ] + }, + { + "cell_type": "code", + "execution_count": 186, + "id": "c14a13eb", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "#strain_profile.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 187, + "id": "ff484767", + "metadata": {}, + "outputs": [], + "source": [ + "#strain_profile" + ] + }, + { + "cell_type": "code", + "execution_count": 188, + "id": "5ab72211", + "metadata": {}, + "outputs": [], + "source": [ + "strain_profile.to_csv(output_file,na_rep='NA',index=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 189, + "id": "020dbe85", + "metadata": {}, + "outputs": [], + "source": [ + "# Open a file with access mode 'a'\n", + "with open(output_file, \"a\") as file_object:\n", + " # Append 'hello' at the end of file\n", + " file_object.write(\"Note: \\n1. 'MDR': Multidrug-resistant, 'XDR': Extensively drug-resistant, 'TDR':totally drug resistant, NA': Data Not Available.\\n2. 'Strain could not be classified' numbers follow the format as ('Number of antibiotics categories count as Intermediate' | 'Number of antibiotics categories count as NA')\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9c17e66a", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff -r 306236ec0511 -r 683299422575 asist_dynamic.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/asist_dynamic.py Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,190 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[1309]: + + +#ASIST program for phenotype based on Antibiotics profile +# create a profile based on selected antibiotics only +# rakesh4osdd@gmail.com, 14-June-2021 + + +# In[1403]: + + +import pandas as pd +import sys +import os +from collections import Counter + + +# In[ ]: + + +input_file=sys.argv[1] +output_file=sys.argv[2] + + +# In[1362]: + + +# strain_profile to phenotype condition +def s_phen(sus,res,na,pb_sus): + if (sus>0 and res==0 and na>=0): + #print('Possible Susceptible') + phen='Possible Susceptible' + elif (sus>=0 and 3<=res<7 and na>=0 and pb_sus==0): + #print('Possible MDR') + phen='Possible MDR' + elif (sus>=0 and 7<=res<9 and na>=0 and pb_sus==0): + #print('Possible XDR') + phen='Possible XDR' + #special cases + elif (sus>=1 and res>0 and na>=0 and pb_sus==1): + #print('Possible XDR') + phen='Possible XDR' + #special cases + elif (sus>0 and res==9 and na>=0): + #print('Possible XDR') + phen='Possible XDR' + elif (sus==0 and res==9 and na>=0): + #print('Possible TDR') + phen='Possible TDR' + else: + #print('Strain could not be classified') + phen='Strain could not be classified' + return(phen) + +#print(s_phen(1,9,0,0)) + + +# In[1363]: + + +# define Antibiotic groups as per antibiotic of CLSI breakpoints MIC +#Aminoglycoside +cat1=['Amikacin','Tobramycin','Gentamycin','Netilmicin'] +#Beta-lactams- Carbapenems +cat2=['Imipenem','Meropenam','Doripenem'] +#Fluoroquinolone +cat3=['Ciprofloxacin','Levofloxacin'] +#Beta-lactam inhibitor +cat4=['Piperacillin/tazobactam','Ticarcillin/clavulanicacid'] +#Cephalosporin +cat5=['Cefotaxime','Ceftriaxone','Ceftazidime','Cefepime'] +#Sulfonamides +cat6=['Trimethoprim/sulfamethoxazole'] +#Penicillins/beta-lactamase +cat7=['Ampicillin/sulbactam'] +#Polymyxins +cat8=['Colistin','Polymyxinb'] +#Tetracycline +cat9=['Tetracycline','Doxicycline','Minocycline'] + +def s_profiler(pd_series): + #print(type(pd_series),'\n', pd_series) + #create a dictionary of dataframe series + cats={'s1':cat1,'s2':cat2,'s3':cat3,'s4':cat4,'s5':cat5,'s6':cat6,'s7':cat7,'s8':cat8,'s9':cat9} + # find the antibiotics name in input series + for cat in cats: + #print(cats[cat]) + cats[cat]=pd_series.filter(cats[cat]) + #print(cats[cat]) + #define res,sus,na,pb_sus + res=0 + sus=0 + na=0 + pb_sus=0 + # special case of 'Polymyxin b' for its value + if 'Polymyxinb' in pd_series: + ctp=cats['s8']['Polymyxinb'].strip().lower() + if ctp == 'susceptible': + pb_sus=1 + #print((ctp,p_sus)) + # check all categories + for cat in cats: + #ctp=cats['s8'].iloc[i:i+1].stack().value_counts().to_dict() + #print(ctp) + # Pandas series + ct=cats[cat].value_counts().to_dict() + #print(ct) + # remove whitespace and convert to lowercase words + ct = {k.strip().lower(): v for k, v in ct.items()} + #print(ct) + k=Counter(ct) + #j=Counter(ct)+Counter(j) + #print(j) + # category wise marking + if k['resistant']>=1: + res=res+1 + if k['susceptible']>=1: + sus=sus+1 + if k['na']>=1: + na=na+1 + #print(s_phen(sus,res,na,pb_sus)) + return(s_phen(sus,res,na,pb_sus)) + + +# In[1397]: + + +#input_file='input2.csv_table.csv' +#output_file=input_file+'_output.txt' +strain_profile=pd.read_csv(input_file, sep=',',na_filter=False,skipinitialspace = True) + + +# In[1387]: + + +old_strain_name=strain_profile.columns[0] +new_strain_name=old_strain_name.capitalize().strip().replace(' ', '') + + +# In[1388]: + + +# make header capitalization, remove leading,lagging, and multiple whitespace for comparision +strain_profile.columns=strain_profile.columns.str.capitalize().str.strip().str.replace('\s+', '', regex=True) +#print(strain_profile.columns) +#strain_profile.head() +#strain_profile.columns + + +# In[1389]: + + +# add new column in dataframe on second position +strain_profile.insert(1, 'Strain phenotype','') +#strain_profile.head() + + +# In[1390]: + + +strain_profile['Strain phenotype'] = strain_profile.apply(lambda x: (s_profiler(x)), axis=1) + + +# In[1391]: + + +#strain_profile.head() + + +# In[1392]: + + +#rename headers for old name +strain_profile=strain_profile.rename(columns = {new_strain_name:old_strain_name, 'Ticarcillin/clavulanicacid':'Ticarcillin/ clavulanic acid','Piperacillin/tazobactam':'Piperacillin/ tazobactam','Trimethoprim/sulfamethoxazole': 'Trimethoprim/ sulfamethoxazole','Ampicillin/sulbactam':'Ampicillin/ sulbactam', 'Polymyxinb': 'Polymyxin B'} ) + + +# In[1404]: + + +#strain_profile + + +# In[1394]: + + +strain_profile.to_csv(output_file,na_rep='NA',index=False) + diff -r 306236ec0511 -r 683299422575 clsi.csv --- a/clsi.csv Fri Jun 11 13:20:08 2021 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,23 +0,0 @@ -Antibiotics,Susceptible,Resistant,Intermediate -Amikacin,≤ 16,≥ 64,32 -Tobramycin,≤ 4,≥ 16,8 -Gentamicin,≤ 4,≥ 16,8 -Netilmicin,≤ 8,≥ 32,16 -Imipenem,≤ 2,≥ 8,4 -Meropenem,≤ 2,≥ 8,4 -Doripenem,≤ 2,≥ 8,4 -Ciprofloxacin,≤ 1,≥ 4,2 -Levofloxacin,≤ 2,≥ 8,4 -Piperacillin/ tazobactam,≤ 16/4,≥ 128/4,32/4-64/4 -Ticarcillin/ clavulanic acid,≤ 16/2,≥ 128/2,32/2-64/2 -Cefotaxime,≤ 8,≥ 64,16-32 -Ceftriaxone,≤ 8,≥ 64,16-32 -Ceftazidime,≤ 8,≥ 32,16 -Cefepime,≤ 8,≥ 32,16 -Trimethoprim/ sulfamethoxazole,≤ 2/38,≥ 4/76,- -Ampicillin/ sulbactam,≤ 8/4,≥ 32/16,16/8 -Colistin,-,≥ 4,≤ 2 -Polymyxin B,-,≥ 4,≤ 2 -Tetracycline,≤ 4,≥ 16,8 -Doxycycline,≤ 4,≥ 16,8 -Minocycline,≤ 4,≥ 16,8 \ No newline at end of file diff -r 306236ec0511 -r 683299422575 clsi_profile.py --- a/clsi_profile.py Fri Jun 11 13:20:08 2021 +0000 +++ b/clsi_profile.py Tue Jun 29 05:20:41 2021 +0000 @@ -282,7 +282,7 @@ # In[229]: -result_selected.insert(0,'Resistance_phenotype','') +#result_selected.insert(0,'Resistance_phenotype','') # In[230]: diff -r 306236ec0511 -r 683299422575 clsi_profile.xml --- a/clsi_profile.xml Fri Jun 11 13:20:08 2021 +0000 +++ b/clsi_profile.xml Tue Jun 29 05:20:41 2021 +0000 @@ -21,7 +21,7 @@ - + @@ -45,6 +45,40 @@ + + @ARTICLE{Sharma_2021, + author = {Tina Sharma and Rakesh Kumar and Anshu Bhardwaj}, + title = {ASIST: Antimicrobial Susceptibility standards based phenotypes}, + journal = {}, + year = {2021}, + volume = {}, + pages = {}, + url = {https://ab-openlab.csir.res.in/asist} + } + + diff -r 306236ec0511 -r 683299422575 clsi_profile_type2.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/clsi_profile_type2.py Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,244 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[1245]: + + +# ASIST module2 | map AST result to the CLSI breakporints with combination antibiotics +# By rakesh4osdd@gmail.com, 06-Jun-2021 +import pandas as pd +import re +import sys + + +# In[1246]: + + +# cross check MIC values +def sus_res(mic): + #print(mic) + #print ((mic,pd.isna(mic[1]),pd.isna(mic[0]),'\n') + if not (pd.isna(mic[0]) or pd.isna(mic[1]) or pd.isna(mic[2])):#check for NaN value + #remove unwanted whitespace + o_mic = mic[0].replace(' ', '') + s_mic = mic[1].replace(' ', '') + r_mic = mic[2].replace(' ', '') + #print (o_mic,s_mic,r_mic) + #print (type(o_mic),type(s_mic),type(r_mic)) + if '/' in s_mic: #check for combination antibiotics + #print ('combination antibiotics') + try: + if '/' in o_mic: + #print ('input combination') + if (float(o_mic.split('/')[0]) <= float(s_mic.split('/')[0]) and float(o_mic.split('/')[1]) <= float(s_mic.split('/')[1])): + strain_type='Susceptible' + elif (float(o_mic.split('/')[0]) >= float(r_mic.split('/')[0]) and float(o_mic.split('/')[1]) >= float(r_mic.split('/')[1])): + strain_type='Resistant' + else: + strain_type='Intermediate' + else: + #print ('single') + if float(o_mic)==0: + strain_type='Strain could not classified' + elif (float(o_mic.split('/')[0]) <= float(s_mic.split('/')[0]) and float(1) <= float(s_mic.split('/')[1])): + strain_type='Susceptible' + elif (float(o_mic.split('/')[0]) >= float(r_mic.split('/')[0]) and float(1) >= float(r_mic.split('/')[1])): + strain_type='Resistant' + else: + strain_type='Intermediate' + except ValueError: + strain_type='Strain could not classified' + else: #single antibiotics + #print('single antibiotics') + if o_mic: + if float(o_mic)==0: + strain_type='Strain could not classified' + elif (float(o_mic) <= float(s_mic)): + strain_type='Susceptible' + elif (float(o_mic) >= float(r_mic)): + strain_type='Resistant' + else: + strain_type='Intermediate' + else: + strain_type='Strain could not classified' + else: + strain_type='Strain could not classified' + return(strain_type) + + +# In[ ]: + +# for input argument +input_user = sys.argv[1] +input_clsi = sys.argv[2] +output_table = sys.argv[3] + +# In[1247]: + + +""" +input_user='input_ast_comb2.csv' +input_clsi='clsi_profile_comb.csv' +output_profile=input_user+'_profile.csv' +output_table=input_user+'_table.csv' + +""" + +# In[1248]: + + +# 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[1249]: + + +clsi_bp=pd.read_csv(input_clsi,sep=',') + + +# In[1290]: + + +#clsi_bp.head(2) +#strain_mic + + +# In[1251]: + + +# 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))) + + +# In[1252]: + + +# 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[1289]: + + +#strain_mic.head() + + +# In[1254]: + + +# 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[1255]: + + +#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']] +except KeyError: + print('Waring: Error in input Values') + + +# In[1256]: + + +#compare MIC values and assign Susceptible and Resistant to Strain +#try: +result[['CLSI_profile']] = result[['o_mic','s_mic','r_mic']].apply(sus_res,axis = 1) +#except ValueError: +# print('Waring: Error in input MIC value') + + +# In[1288]: + + +#result + + +# In[1258]: + + +#result[['Strain name', 'Antibiotics', 'MIC','s_mic','r_mic','CLSI_profile']].to_csv(output_profile,sep=',', index=False, encoding='utf-8-sig') + + +# In[1259]: + + +#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[1261]: + + +result_table + + +# In[1264]: + + +#result_table.to_csv(output_table,na_rep='NA') + + +# In[1282]: + + +# 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[1283]: + + +result_selected.shape + + +# In[1284]: + + +result_table.shape + + +# In[1285]: + + +result_selected.insert(0,'Resistance_phenotype','') + + +# In[1286]: + + +result_selected.to_csv(output_table,na_rep='NA') + + +# In[1287]: + + +#rename headers +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[ ]: + + + + + +# In[ ]: + + + + diff -r 306236ec0511 -r 683299422575 clsi_profile_type2_linux-Copy1.ipynb --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/clsi_profile_type2_linux-Copy1.ipynb Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,2461 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "967b1345", + "metadata": {}, + "outputs": [], + "source": [ + "# ASIST module2 | map AST result to the CLSI breakporints with combination antibiotics\n", + "# By rakesh4osdd@gmail.com, 06-Jun-2021\n", + "import pandas as pd\n", + "import re\n", + "import sys" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "39e25c15", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.2.4 2.2.1\n" + ] + } + ], + "source": [ + "print(pd.__version__, re.__version__)" + ] + }, + { + "cell_type": "code", + "execution_count": 175, + "id": "c96d7c62", + "metadata": {}, + "outputs": [], + "source": [ + "# cross check MIC values\n", + "def sus_res(mic):\n", + " print(mic)\n", + " #print ((mic,pd.isna(mic[1]),pd.isna(mic[0]),'\\n')\n", + " if not (pd.isna(mic[0]) or pd.isna(mic[1]) or pd.isna(mic[2])):#check for NaN value\n", + " #remove unwanted whitespace\n", + " o_mic = mic[0].replace(' ', '')\n", + " s_mic = mic[1].replace(' ', '')\n", + " r_mic = mic[2].replace(' ', '')\n", + " i_mic = mic[3].replace(' ', '')\n", + " print(imic(o_mic,i_mic))\n", + " #print (o_mic,s_mic,r_mic)\n", + " #print (type(o_mic),type(s_mic),type(r_mic))\n", + " if '/' in s_mic: #check for combination antibiotics\n", + " #print ('combination antibiotics')\n", + " try:\n", + " if '/' in o_mic:\n", + " #print ('input combination')\n", + " if (float(o_mic.split('/')[0]) <= float(s_mic.split('/')[0]) and float(o_mic.split('/')[1]) <= float(s_mic.split('/')[1])):\n", + " strain_type='Susceptible'\n", + " elif (float(o_mic.split('/')[0]) >= float(r_mic.split('/')[0]) and float(o_mic.split('/')[1]) >= float(r_mic.split('/')[1])):\n", + " strain_type='Resistant'\n", + " elif (imic(o_mic,i_mic)):\n", + " strain_type='Intermediate-1' \n", + " else:\n", + " strain_type='Intermediate-2'\n", + " else: \n", + " #print ('single')\n", + " if float(o_mic)==0:\n", + " strain_type='Strain could not classified'\n", + " elif (float(o_mic.split('/')[0]) <= float(s_mic.split('/')[0]) and float(1) <= float(s_mic.split('/')[1])):\n", + " strain_type='Susceptible'\n", + " elif (float(o_mic.split('/')[0]) >= float(r_mic.split('/')[0]) and float(1) >= float(r_mic.split('/')[1])):\n", + " strain_type='Resistant'\n", + " else:\n", + " strain_type='Intermediate-3'\n", + " except ValueError:\n", + " strain_type='Strain could not classified-1'\n", + " elif (s_mic == '-'):\n", + " if o_mic:\n", + " if float(o_mic)==0:\n", + " strain_type='Strain could not classified-2'\n", + " #elif (float(o_mic) <= float(s_mic)):\n", + " # strain_type='Susceptible'\n", + " elif (float(o_mic) >= float(r_mic)):\n", + " strain_type='Resistant'\n", + " elif (imic(o_mic,i_mic)):\n", + " strain_type='Intermediat-4'\n", + " else:\n", + " strain_type='Intermediate-5'\n", + " else:\n", + " strain_type='Strain could not classified-3'\n", + " else: #single antibiotics\n", + " #print('single antibiotics')\n", + " if o_mic:\n", + " if float(o_mic)==0:\n", + " strain_type='Strain could not classified-4'\n", + " elif (float(o_mic) <= float(s_mic)):\n", + " strain_type='Susceptible'\n", + " elif (float(o_mic) >= float(r_mic)):\n", + " strain_type='Resistant'\n", + " else:\n", + " strain_type='Intermediate-6'\n", + " else:\n", + " strain_type='Strain could not classified-5'\n", + " else:\n", + " strain_type='Strain could not classified-6'\n", + " return(strain_type)" + ] + }, + { + "cell_type": "code", + "execution_count": 176, + "id": "dbc70e34", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['32/2', '16/4', '128/4', '32/4-64/4']\n", + "32/2 32/4-64/4\n", + "False\n", + "32/2 32/4-64/4\n" + ] + }, + { + "data": { + "text/plain": [ + "'Intermediate-2'" + ] + }, + "execution_count": 176, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mic=['32/2','16/4','128/4','32/4-64/4']\n", + "sus_res(mic)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "653b096e", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 202, + "id": "626a1e3f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "65/4 64/4 s\n", + "65 4 64 4 s\n" + ] + }, + { + "data": { + "text/plain": [ + "'Strain could not classified-5'" + ] + }, + "execution_count": 202, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def check_mic(mic1,mic2,mic_type):\n", + " print(mic1,mic2,mic_type)\n", + " m1a = mic1.split('/')[0]\n", + " m1b = mic1.split('/')[1]\n", + " if '-' in mic2: # for intermediate only\n", + " m2a = mic2.split('-')[0].split('/')[0]\n", + " m2b = mic2.split('-')[0].split('/')[1]\n", + " m2aa = mic2.split('-')[1].split('/')[0]\n", + " m2bb = mic2.split('-')[1].split('/')[1]\n", + " if (float(m2aa)>=float(m1a)>=float(m2a) and float(m2b)>=float(m1b)>=float(m2b)):\n", + " #print('intermediate')\n", + " mic_type='Intermediate-1'\n", + " else:\n", + " #print('not define')\n", + " mic_type='Strain could not classified-1'\n", + " #print (m1a,m1b,m2a,m2b,m2aa,m2bb)\n", + " else:\n", + " m2a = mic2.split('/')[0]\n", + " m2b = mic2.split('/')[1]\n", + " print(m1a,m1b,m2a,m2b,mic_type)\n", + " if mic_type=='s':\n", + " if (float(m1a)<=float(m2a) and float(m1b)<=float(m2b)):\n", + " mic_type='Susceptible'\n", + " else:\n", + " mic_type='Strain could not classified-5'\n", + " elif mic_type=='r':\n", + " if (float(m1a)>=float(m2a) and float(m1b)>=float(m2b)):\n", + " mic_type='Resistant'\n", + " else:\n", + " mic_type='Strain could not classified-4'\n", + " elif mic_type=='i':\n", + " if (float(m1a)==float(m2a) and float(m1b)==float(m2b)):\n", + " mic_type='Intermediate-2'\n", + " else:\n", + " mic_type='Strain could not classified-3'\n", + " else:\n", + " mic_type='Strain could not classified-2'\n", + " return(mic_type)\n", + " \n", + "check_mic('65/4','64/4','s')\n", + "# float(mic1.split('/')[0]) <= float(mic2.split('/')[0]) and float(mic1.split('/')[1]) <= float(mic2.split('/')[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 171, + "id": "19905924", + "metadata": {}, + "outputs": [], + "source": [ + "#compare MIC values and assign Susceptible and Resistant to Strain\n", + "#try:\n", + "#result[['CLSI_profile']] = result[['o_mic','s_mic','r_mic','i_mic']].apply(sus_res,axis = 1)\n", + "#except ValueError:\n", + "# print('Waring: Error in input MIC value')\n", + "#result[['o_mic','s_mic','r_mic','i_mic']].apply(sus_res,axis = 1)\n", + "#del result['CLSI_profile']" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "7784b77d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'input_user = sys.argv[1]\\ninput_clsi = sys.argv[2]\\noutput_table = sys.argv[3]'" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# for input argument\n", + "\"\"\"input_user = sys.argv[1]\n", + "input_clsi = sys.argv[2]\n", + "output_table = sys.argv[3]\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "1dee9127", + "metadata": {}, + "outputs": [], + "source": [ + "input_user='input.csv'\n", + "input_clsi='clsi.csv'\n", + "output_profile=input_user+'_profile.csv'\n", + "output_table=input_user+'_table.csv'" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "14c5cfd3", + "metadata": {}, + "outputs": [], + "source": [ + "# read user AST data with selected 3 columns\n", + "strain_mic=pd.read_csv(input_user, sep=',', usecols =['Strain name', 'Antibiotics', 'MIC'],na_filter=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "77135cb7", + "metadata": {}, + "outputs": [], + "source": [ + "clsi_bp=pd.read_csv(input_clsi,sep=',')" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "2ec1cbec", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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AntibioticsSusceptibleResistantIntermediate
0Amikacin≤ 16≥ 6432
1Tobramycin≤ 4≥ 168
2Gentamicin≤ 4≥ 168
3Netilmicin≤ 8≥ 3216
4Imipenem≤ 2≥ 84
5Meropenem≤ 2≥ 84
6Doripenem≤ 2≥ 84
7Ciprofloxacin≤ 1≥ 42
8Levofloxacin≤ 2≥ 84
9Piperacillin/ tazobactam≤ 16/4≥ 128/432/4-64/4
10Ticarcillin/ clavulanic acid≤ 16/2≥ 128/232/2-64/2
11Cefotaxime≤ 8≥ 6416-32
12Ceftriaxone≤ 8≥ 6416-32
13Ceftazidime≤ 8≥ 3216
14Cefepime≤ 8≥ 3216
15Trimethoprim/ sulfamethoxazole≤ 2/38≥ 4/76-
16Ampicillin/ sulbactam≤ 8/4≥ 32/1616/8
17Colistin-≥ 4≤ 2
18Polymyxin B-≥ 4≤ 2
19Tetracycline≤ 4≥ 168
20Doxycycline≤ 4≥ 168
21Minocycline≤ 4≥ 168
\n", + "
" + ], + "text/plain": [ + " Antibiotics Susceptible Resistant Intermediate\n", + "0 Amikacin ≤ 16 ≥ 64 32\n", + "1 Tobramycin ≤ 4 ≥ 16 8\n", + "2 Gentamicin ≤ 4 ≥ 16 8\n", + "3 Netilmicin ≤ 8 ≥ 32 16\n", + "4 Imipenem ≤ 2 ≥ 8 4\n", + "5 Meropenem ≤ 2 ≥ 8 4\n", + "6 Doripenem ≤ 2 ≥ 8 4\n", + "7 Ciprofloxacin ≤ 1 ≥ 4 2\n", + "8 Levofloxacin ≤ 2 ≥ 8 4\n", + "9 Piperacillin/ tazobactam ≤ 16/4 ≥ 128/4 32/4-64/4\n", + "10 Ticarcillin/ clavulanic acid ≤ 16/2 ≥ 128/2 32/2-64/2\n", + "11 Cefotaxime ≤ 8 ≥ 64 16-32\n", + "12 Ceftriaxone ≤ 8 ≥ 64 16-32\n", + "13 Ceftazidime ≤ 8 ≥ 32 16\n", + "14 Cefepime ≤ 8 ≥ 32 16\n", + "15 Trimethoprim/ sulfamethoxazole ≤ 2/38 ≥ 4/76 -\n", + "16 Ampicillin/ sulbactam ≤ 8/4 ≥ 32/16 16/8\n", + "17 Colistin - ≥ 4 ≤ 2\n", + "18 Polymyxin B - ≥ 4 ≤ 2\n", + "19 Tetracycline ≤ 4 ≥ 16 8\n", + "20 Doxycycline ≤ 4 ≥ 16 8\n", + "21 Minocycline ≤ 4 ≥ 16 8" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "clsi_bp\n", + "#strain_mic" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "860505f7", + "metadata": {}, + "outputs": [], + "source": [ + "# convert MIC to numbers sMIC, rMIC\n", + "clsi_bp['s_mic'] =clsi_bp[['Susceptible']].applymap(lambda x: (re.sub(r'[^0-9.\\/-]', '', x)))\n", + "clsi_bp['r_mic'] =clsi_bp[['Resistant']].applymap(lambda x: (re.sub(r'[^0-9.\\/-]', '', x)))\n", + "clsi_bp['i_mic'] = clsi_bp[['Intermediate']].applymap(lambda x: (re.sub(r'[^0-9.\\/-]', '', x)))" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "cad964a6", + "metadata": {}, + "outputs": [], + "source": [ + "#clsi_bp['i_mic'] = clsi_bp[['Intermediate']].applymap(lambda x: (re.sub(r'[^0-9.\\/-]', '', x)))" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "2b6c02f5", + "metadata": {}, + "outputs": [], + "source": [ + "# Read only numbers in MIC values\n", + "#try:\n", + "strain_mic['o_mic']=strain_mic[['MIC']].applymap(lambda x: (re.sub(r'[^0-9.\\/]','', x)))\n", + "#except TypeError:\n", + "# print('Waring: Error in MIC value')" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "942fefb2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Strain nameAntibioticsMICo_mic
0Acinetobacter baumannii A85Colistin0.10.1
1Acinetobacter baumannii A85Colistin11
2Acinetobacter baumannii A85Colistin22
3Acinetobacter baumannii AB307-0294Ampicillin00
4Acinetobacter baumannii AB307-0294Ampicillin/sulbactammg/L/
5Acinetobacter baumannii AB307-0294Piperacillin/tazobactam00
6Acinetobacter baumannii AB307-0294Cefazolin6464
7Acinetobacter baumannii AB307-0294Ceftriaxone1616
8Acinetobacter baumannii AB307-0294Cefepime88
9Acinetobacter baumannii AB307-0294Meropenem0.250.25
10Acinetobacter baumannii AB307-0294Imipenem11
11Acinetobacter baumannii AB307-0294Tigecycline0.50.5
12Acinetobacter baumannii AB5075-UWCeftazidime>128128
13Acinetobacter baumannii AB5075-UWCefepime>256256
14Acinetobacter baumannii AB5075-UWCiprofloxacin>3232
15Acinetobacter baumannii DU202Colistin
16Acinetobacter baumannii DU202Trimethoprim/sulfamethoxazole8/1528/152
17Acinetobacter baumannii DU202Ampicillin/sulbactam>=0.3 mg/L0.3/
18Acinetobacter baumannii DU202Ticarcillin/clavulanicacid>=128/2128/2
19Acinetobacter baumannii DU202Piperacillin/tazobactamNA
20Acinetobacter baumannii DU202Trimethoprim/sulfamethoxazole8/1528/152
21Acinetobacter baumannii ORAB01Piperacillin/tazobactam>64/464/4
22Acinetobacter baumannii strain MRSN7100Amoxicillin/clavulanicacid16/816/8
23Acinetobacter baumannii strain MRSN7168Amoxicillin/clavulanicacid16/816/8
24Acinetobacter baumannii strain MRSN7336Amoxicillin/clavulanicacid16/816/8
25Acinetobacter baumannii strain MRSN7834Amoxicillin/clavulanicacid16/816/8
26Acinetobacter baumannii strain FDA-CDC-AR_0305Polymyxinb11
27Acinetobacter baumannii strain FDA-CDC-AR_0306Polymyxinb11
28Acinetobacter baumannii strain FDA-CDC-AR_0307Polymyxinb88
29Acinetobacter baumannii strain FDA-CDC-AR_0308Polymyxinb44
\n", + "
" + ], + "text/plain": [ + " Strain name \\\n", + "0 Acinetobacter baumannii A85 \n", + "1 Acinetobacter baumannii A85 \n", + "2 Acinetobacter baumannii A85 \n", + "3 Acinetobacter baumannii AB307-0294 \n", + "4 Acinetobacter baumannii AB307-0294 \n", + "5 Acinetobacter baumannii AB307-0294 \n", + "6 Acinetobacter baumannii AB307-0294 \n", + "7 Acinetobacter baumannii AB307-0294 \n", + "8 Acinetobacter baumannii AB307-0294 \n", + "9 Acinetobacter baumannii AB307-0294 \n", + "10 Acinetobacter baumannii AB307-0294 \n", + "11 Acinetobacter baumannii AB307-0294 \n", + "12 Acinetobacter baumannii AB5075-UW \n", + "13 Acinetobacter baumannii AB5075-UW \n", + "14 Acinetobacter baumannii AB5075-UW \n", + "15 Acinetobacter baumannii DU202 \n", + "16 Acinetobacter baumannii DU202 \n", + "17 Acinetobacter baumannii DU202 \n", + "18 Acinetobacter baumannii DU202 \n", + "19 Acinetobacter baumannii DU202 \n", + "20 Acinetobacter baumannii DU202 \n", + "21 Acinetobacter baumannii ORAB01 \n", + "22 Acinetobacter baumannii strain MRSN7100 \n", + "23 Acinetobacter baumannii strain MRSN7168 \n", + "24 Acinetobacter baumannii strain MRSN7336 \n", + "25 Acinetobacter baumannii strain MRSN7834 \n", + "26 Acinetobacter baumannii strain FDA-CDC-AR_0305 \n", + "27 Acinetobacter baumannii strain FDA-CDC-AR_0306 \n", + "28 Acinetobacter baumannii strain FDA-CDC-AR_0307 \n", + "29 Acinetobacter baumannii strain FDA-CDC-AR_0308 \n", + "\n", + " Antibiotics MIC o_mic \n", + "0 Colistin 0.1 0.1 \n", + "1 Colistin 1 1 \n", + "2 Colistin 2 2 \n", + "3 Ampicillin 0 0 \n", + "4 Ampicillin/sulbactam mg/L / \n", + "5 Piperacillin/tazobactam 0 0 \n", + "6 Cefazolin 64 64 \n", + "7 Ceftriaxone 16 16 \n", + "8 Cefepime 8 8 \n", + "9 Meropenem 0.25 0.25 \n", + "10 Imipenem 1 1 \n", + "11 Tigecycline 0.5 0.5 \n", + "12 Ceftazidime >128 128 \n", + "13 Cefepime >256 256 \n", + "14 Ciprofloxacin >32 32 \n", + "15 Colistin \n", + "16 Trimethoprim/sulfamethoxazole 8/152 8/152 \n", + "17 Ampicillin/sulbactam >=0.3 mg/L 0.3/ \n", + "18 Ticarcillin/clavulanicacid >=128/2 128/2 \n", + "19 Piperacillin/tazobactam NA \n", + "20 Trimethoprim/sulfamethoxazole 8/152 8/152 \n", + "21 Piperacillin/tazobactam >64/4 64/4 \n", + "22 Amoxicillin/clavulanicacid 16/8 16/8 \n", + "23 Amoxicillin/clavulanicacid 16/8 16/8 \n", + "24 Amoxicillin/clavulanicacid 16/8 16/8 \n", + "25 Amoxicillin/clavulanicacid 16/8 16/8 \n", + "26 Polymyxinb 1 1 \n", + "27 Polymyxinb 1 1 \n", + "28 Polymyxinb 8 8 \n", + "29 Polymyxinb 4 4 " + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "strain_mic" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "bba6b0a2", + "metadata": {}, + "outputs": [], + "source": [ + "# capitalize each Antibiotic Name for comparision with removing whitespace\n", + "strain_mic['Antibiotics']=strain_mic['Antibiotics'].str.capitalize().str.replace(\" \",\"\")\n", + "clsi_bp['Antibiotics']=clsi_bp['Antibiotics'].str.capitalize().str.replace(\" \",\"\")" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "ea403928", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Strain nameAntibioticsMICo_mics_micr_mici_mic
0Acinetobacter baumannii A85Colistin0.10.1-42
1Acinetobacter baumannii A85Colistin11-42
2Acinetobacter baumannii A85Colistin22-42
3Acinetobacter baumannii DU202Colistin-42
4Acinetobacter baumannii AB307-0294Ampicillin/sulbactammg/L/8/432/1616/8
5Acinetobacter baumannii DU202Ampicillin/sulbactam>=0.3 mg/L0.3/8/432/1616/8
6Acinetobacter baumannii AB307-0294Piperacillin/tazobactam0016/4128/432/4-64/4
7Acinetobacter baumannii DU202Piperacillin/tazobactamNA16/4128/432/4-64/4
8Acinetobacter baumannii ORAB01Piperacillin/tazobactam>64/464/416/4128/432/4-64/4
9Acinetobacter baumannii AB307-0294Ceftriaxone161686416-32
10Acinetobacter baumannii AB307-0294Cefepime8883216
11Acinetobacter baumannii AB5075-UWCefepime>25625683216
12Acinetobacter baumannii AB307-0294Meropenem0.250.25284
13Acinetobacter baumannii AB307-0294Imipenem11284
14Acinetobacter baumannii AB5075-UWCeftazidime>12812883216
15Acinetobacter baumannii AB5075-UWCiprofloxacin>3232142
16Acinetobacter baumannii DU202Trimethoprim/sulfamethoxazole8/1528/1522/384/76-
17Acinetobacter baumannii DU202Trimethoprim/sulfamethoxazole8/1528/1522/384/76-
18Acinetobacter baumannii DU202Ticarcillin/clavulanicacid>=128/2128/216/2128/232/2-64/2
19Acinetobacter baumannii strain FDA-CDC-AR_0305Polymyxinb11-42
20Acinetobacter baumannii strain FDA-CDC-AR_0306Polymyxinb11-42
21Acinetobacter baumannii strain FDA-CDC-AR_0307Polymyxinb88-42
22Acinetobacter baumannii strain FDA-CDC-AR_0308Polymyxinb44-42
\n", + "
" + ], + "text/plain": [ + " Strain name \\\n", + "0 Acinetobacter baumannii A85 \n", + "1 Acinetobacter baumannii A85 \n", + "2 Acinetobacter baumannii A85 \n", + "3 Acinetobacter baumannii DU202 \n", + "4 Acinetobacter baumannii AB307-0294 \n", + "5 Acinetobacter baumannii DU202 \n", + "6 Acinetobacter baumannii AB307-0294 \n", + "7 Acinetobacter baumannii DU202 \n", + "8 Acinetobacter baumannii ORAB01 \n", + "9 Acinetobacter baumannii AB307-0294 \n", + "10 Acinetobacter baumannii AB307-0294 \n", + "11 Acinetobacter baumannii AB5075-UW \n", + "12 Acinetobacter baumannii AB307-0294 \n", + "13 Acinetobacter baumannii AB307-0294 \n", + "14 Acinetobacter baumannii AB5075-UW \n", + "15 Acinetobacter baumannii AB5075-UW \n", + "16 Acinetobacter baumannii DU202 \n", + "17 Acinetobacter baumannii DU202 \n", + "18 Acinetobacter baumannii DU202 \n", + "19 Acinetobacter baumannii strain FDA-CDC-AR_0305 \n", + "20 Acinetobacter baumannii strain FDA-CDC-AR_0306 \n", + "21 Acinetobacter baumannii strain FDA-CDC-AR_0307 \n", + "22 Acinetobacter baumannii strain FDA-CDC-AR_0308 \n", + "\n", + " Antibiotics MIC o_mic s_mic r_mic i_mic \n", + "0 Colistin 0.1 0.1 - 4 2 \n", + "1 Colistin 1 1 - 4 2 \n", + "2 Colistin 2 2 - 4 2 \n", + "3 Colistin - 4 2 \n", + "4 Ampicillin/sulbactam mg/L / 8/4 32/16 16/8 \n", + "5 Ampicillin/sulbactam >=0.3 mg/L 0.3/ 8/4 32/16 16/8 \n", + "6 Piperacillin/tazobactam 0 0 16/4 128/4 32/4-64/4 \n", + "7 Piperacillin/tazobactam NA 16/4 128/4 32/4-64/4 \n", + "8 Piperacillin/tazobactam >64/4 64/4 16/4 128/4 32/4-64/4 \n", + "9 Ceftriaxone 16 16 8 64 16-32 \n", + "10 Cefepime 8 8 8 32 16 \n", + "11 Cefepime >256 256 8 32 16 \n", + "12 Meropenem 0.25 0.25 2 8 4 \n", + "13 Imipenem 1 1 2 8 4 \n", + "14 Ceftazidime >128 128 8 32 16 \n", + "15 Ciprofloxacin >32 32 1 4 2 \n", + "16 Trimethoprim/sulfamethoxazole 8/152 8/152 2/38 4/76 - \n", + "17 Trimethoprim/sulfamethoxazole 8/152 8/152 2/38 4/76 - \n", + "18 Ticarcillin/clavulanicacid >=128/2 128/2 16/2 128/2 32/2-64/2 \n", + "19 Polymyxinb 1 1 - 4 2 \n", + "20 Polymyxinb 1 1 - 4 2 \n", + "21 Polymyxinb 8 8 - 4 2 \n", + "22 Polymyxinb 4 4 - 4 2 " + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#compare CLSI Antibiotics only\n", + "#result=pd.merge(strain_mic, clsi_bp, on='Antibiotics',how='inner', indicator=True)[['Strain name','Antibiotics', 'MIC', 'o_mic', 's_mic', 'r_mic','_merge']]\n", + "try:\n", + " result=pd.merge(strain_mic, clsi_bp, on='Antibiotics',how='inner')[['Strain name','Antibiotics', 'MIC', 'o_mic', 's_mic', 'r_mic','i_mic']]\n", + "except KeyError:\n", + " print('Waring: Error in input Values')\n", + "result" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "44f7e35d", + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "could not broadcast input array from shape (23,) into shape (23,1)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#compare MIC values and assign Susceptible and Resistant to Strain\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;31m#try:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'CLSI_profile'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'o_mic'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m's_mic'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'r_mic'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'i_mic'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msus_res\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0maxis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0;31m#except ValueError:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;31m# print('Waring: Error in input MIC value')\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.9/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__setitem__\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m 3158\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setitem_frame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3159\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mSeries\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3160\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setitem_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3161\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3162\u001b[0m \u001b[0;31m# set column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.9/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_setitem_array\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m 3196\u001b[0m )[1]\n\u001b[1;32m 3197\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_setitem_copy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3198\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m 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\u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1035\u001b[0;31m \u001b[0mvalues\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1036\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1037\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtranspose\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: could not broadcast input array from shape (23,) into shape (23,1)" + ] + } + ], + "source": [ + "#compare MIC values and assign Susceptible and Resistant to Strain\n", + "#try:\n", + "result[['CLSI_profile']] = result[['o_mic','s_mic','r_mic','i_mic']].apply(sus_res,axis = 1)\n", + "#except ValueError:\n", + "# print('Waring: Error in input MIC value')" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "id": "30c2a7a3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Strain nameAntibioticsMICo_mics_micr_mici_micCLSI_profile
0Acinetobacter baumannii A85Colistin0.10.1-42Intermediate
1Acinetobacter baumannii A85Colistin11-42Intermediate
2Acinetobacter baumannii A85Colistin22-42IntermediatE
3Acinetobacter baumannii DU202Colistin-42Strain could not classified
4Acinetobacter baumannii AB307-0294Ampicillin/sulbactammg/L/8/432/1616/8Strain could not classified
5Acinetobacter baumannii DU202Ampicillin/sulbactam>=0.3 mg/L0.3/8/432/1616/8Strain could not classified
6Acinetobacter baumannii AB307-0294Piperacillin/tazobactam0016/4128/432/4-64/4Strain could not classified
7Acinetobacter baumannii DU202Piperacillin/tazobactamNA16/4128/432/4-64/4Strain could not classified
8Acinetobacter baumannii ORAB01Piperacillin/tazobactam>64/464/416/4128/432/4-64/4Intermediate
9Acinetobacter baumannii AB307-0294Ceftriaxone161686416-32Intermediate
10Acinetobacter baumannii AB307-0294Cefepime8883216Susceptible
11Acinetobacter baumannii AB5075-UWCefepime>25625683216Resistant
12Acinetobacter baumannii AB307-0294Meropenem0.250.25284Susceptible
13Acinetobacter baumannii AB307-0294Imipenem11284Susceptible
14Acinetobacter baumannii AB5075-UWCeftazidime>12812883216Resistant
15Acinetobacter baumannii AB5075-UWCiprofloxacin>3232142Resistant
16Acinetobacter baumannii DU202Trimethoprim/sulfamethoxazole8/1528/1522/384/76-Resistant
17Acinetobacter baumannii DU202Trimethoprim/sulfamethoxazole8/1528/1522/384/76-Resistant
18Acinetobacter baumannii DU202Ticarcillin/clavulanicacid>=128/2128/216/2128/232/2-64/2Resistant
19Acinetobacter baumannii strain FDA-CDC-AR_0305Polymyxinb11-42Intermediate
20Acinetobacter baumannii strain FDA-CDC-AR_0306Polymyxinb11-42Intermediate
21Acinetobacter baumannii strain FDA-CDC-AR_0307Polymyxinb88-42Resistant
22Acinetobacter baumannii strain FDA-CDC-AR_0308Polymyxinb44-42Resistant
\n", + "
" + ], + "text/plain": [ + " Strain name \\\n", + "0 Acinetobacter baumannii A85 \n", + "1 Acinetobacter baumannii A85 \n", + "2 Acinetobacter baumannii A85 \n", + "3 Acinetobacter baumannii DU202 \n", + "4 Acinetobacter baumannii AB307-0294 \n", + "5 Acinetobacter baumannii DU202 \n", + "6 Acinetobacter baumannii AB307-0294 \n", + "7 Acinetobacter baumannii DU202 \n", + "8 Acinetobacter baumannii ORAB01 \n", + "9 Acinetobacter baumannii AB307-0294 \n", + "10 Acinetobacter baumannii AB307-0294 \n", + "11 Acinetobacter baumannii AB5075-UW \n", + "12 Acinetobacter baumannii AB307-0294 \n", + "13 Acinetobacter baumannii AB307-0294 \n", + "14 Acinetobacter baumannii AB5075-UW \n", + "15 Acinetobacter baumannii AB5075-UW \n", + "16 Acinetobacter baumannii DU202 \n", + "17 Acinetobacter baumannii DU202 \n", + "18 Acinetobacter baumannii DU202 \n", + "19 Acinetobacter baumannii strain FDA-CDC-AR_0305 \n", + "20 Acinetobacter baumannii strain FDA-CDC-AR_0306 \n", + "21 Acinetobacter baumannii strain FDA-CDC-AR_0307 \n", + "22 Acinetobacter baumannii strain FDA-CDC-AR_0308 \n", + "\n", + " Antibiotics MIC o_mic s_mic r_mic i_mic \\\n", + "0 Colistin 0.1 0.1 - 4 2 \n", + "1 Colistin 1 1 - 4 2 \n", + "2 Colistin 2 2 - 4 2 \n", + "3 Colistin - 4 2 \n", + "4 Ampicillin/sulbactam mg/L / 8/4 32/16 16/8 \n", + "5 Ampicillin/sulbactam >=0.3 mg/L 0.3/ 8/4 32/16 16/8 \n", + "6 Piperacillin/tazobactam 0 0 16/4 128/4 32/4-64/4 \n", + "7 Piperacillin/tazobactam NA 16/4 128/4 32/4-64/4 \n", + "8 Piperacillin/tazobactam >64/4 64/4 16/4 128/4 32/4-64/4 \n", + "9 Ceftriaxone 16 16 8 64 16-32 \n", + "10 Cefepime 8 8 8 32 16 \n", + "11 Cefepime >256 256 8 32 16 \n", + "12 Meropenem 0.25 0.25 2 8 4 \n", + "13 Imipenem 1 1 2 8 4 \n", + "14 Ceftazidime >128 128 8 32 16 \n", + "15 Ciprofloxacin >32 32 1 4 2 \n", + "16 Trimethoprim/sulfamethoxazole 8/152 8/152 2/38 4/76 - \n", + "17 Trimethoprim/sulfamethoxazole 8/152 8/152 2/38 4/76 - \n", + "18 Ticarcillin/clavulanicacid >=128/2 128/2 16/2 128/2 32/2-64/2 \n", + "19 Polymyxinb 1 1 - 4 2 \n", + "20 Polymyxinb 1 1 - 4 2 \n", + "21 Polymyxinb 8 8 - 4 2 \n", + "22 Polymyxinb 4 4 - 4 2 \n", + "\n", + " CLSI_profile \n", + "0 Intermediate \n", + "1 Intermediate \n", + "2 IntermediatE \n", + "3 Strain could not classified \n", + "4 Strain could not classified \n", + "5 Strain could not classified \n", + "6 Strain could not classified \n", + "7 Strain could not classified \n", + "8 Intermediate \n", + "9 Intermediate \n", + "10 Susceptible \n", + "11 Resistant \n", + "12 Susceptible \n", + "13 Susceptible \n", + "14 Resistant \n", + "15 Resistant \n", + "16 Resistant \n", + "17 Resistant \n", + "18 Resistant \n", + "19 Intermediate \n", + "20 Intermediate \n", + "21 Resistant \n", + "22 Resistant " + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "ab7d8379", + "metadata": {}, + "outputs": [], + "source": [ + "#result[['Strain name', 'Antibiotics', 'MIC','s_mic','r_mic','CLSI_profile']].to_csv(output_profile,sep=',', index=False, encoding='utf-8-sig')" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "a426ae2b", + "metadata": {}, + "outputs": [], + "source": [ + "#create a pivot table for ASIST\n", + "table=result[['Strain name', 'Antibiotics','CLSI_profile']].drop_duplicates()\n", + "result_table=pd.pivot_table(table, values ='CLSI_profile', index =['Strain name'],columns =['Antibiotics'], aggfunc = lambda x: ' '.join(x))" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "df439a58", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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AntibioticsAmpicillin/sulbactamCefepimeCeftazidimeCeftriaxoneCiprofloxacinColistinImipenemMeropenemPiperacillin/tazobactamPolymyxinbTicarcillin/clavulanicacidTrimethoprim/sulfamethoxazole
Strain name
Acinetobacter baumannii A85NaNNaNNaNNaNNaNSusceptibleNaNNaNNaNNaNNaNNaN
Acinetobacter baumannii AB307-0294Strain could not classifiedSusceptibleNaNIntermediateNaNNaNSusceptibleSusceptibleStrain could not classifiedNaNNaNNaN
Acinetobacter baumannii AB5075-UWNaNResistantResistantNaNResistantNaNNaNNaNNaNNaNNaNNaN
Acinetobacter baumannii DU202Strain could not classifiedNaNNaNNaNNaNStrain could not classifiedNaNNaNStrain could not classifiedNaNResistantResistant
Acinetobacter baumannii ORAB01NaNNaNNaNNaNNaNNaNNaNNaNIntermediateNaNNaNNaN
Acinetobacter baumannii strain FDA-CDC-AR_0305NaNNaNNaNNaNNaNNaNNaNNaNNaNSusceptibleNaNNaN
Acinetobacter baumannii strain FDA-CDC-AR_0306NaNNaNNaNNaNNaNNaNNaNNaNNaNSusceptibleNaNNaN
Acinetobacter baumannii strain FDA-CDC-AR_0307NaNNaNNaNNaNNaNNaNNaNNaNNaNResistantNaNNaN
Acinetobacter baumannii strain FDA-CDC-AR_0308NaNNaNNaNNaNNaNNaNNaNNaNNaNResistantNaNNaN
\n", + "
" + ], + "text/plain": [ + "Antibiotics Ampicillin/sulbactam \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 Strain could not classified \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 Strain could not classified \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Cefepime Ceftazidime \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN NaN \n", + "Acinetobacter baumannii AB307-0294 Susceptible NaN \n", + "Acinetobacter baumannii AB5075-UW Resistant Resistant \n", + "Acinetobacter baumannii DU202 NaN NaN \n", + "Acinetobacter baumannii ORAB01 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN NaN \n", + "\n", + "Antibiotics Ceftriaxone Ciprofloxacin \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN NaN \n", + "Acinetobacter baumannii AB307-0294 Intermediate NaN \n", + "Acinetobacter baumannii AB5075-UW NaN Resistant \n", + "Acinetobacter baumannii DU202 NaN NaN \n", + "Acinetobacter baumannii ORAB01 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN NaN \n", + "\n", + "Antibiotics Colistin \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 Susceptible \n", + "Acinetobacter baumannii AB307-0294 NaN \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 Strain could not classified \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Imipenem Meropenem \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN NaN \n", + "Acinetobacter baumannii AB307-0294 Susceptible Susceptible \n", + "Acinetobacter baumannii AB5075-UW NaN NaN \n", + "Acinetobacter baumannii DU202 NaN NaN \n", + "Acinetobacter baumannii ORAB01 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN NaN \n", + "\n", + "Antibiotics Piperacillin/tazobactam \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 Strain could not classified \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 Strain could not classified \n", + "Acinetobacter baumannii ORAB01 Intermediate \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Polymyxinb \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 NaN \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 NaN \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 Susceptible \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 Susceptible \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 Resistant \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 Resistant \n", + "\n", + "Antibiotics Ticarcillin/clavulanicacid \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 NaN \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 Resistant \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Trimethoprim/sulfamethoxazole \n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 NaN \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 Resistant \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN " + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result_table" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "ee19e872", + "metadata": {}, + "outputs": [], + "source": [ + "#result_table.to_csv(output_table,na_rep='NA')" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "692ab948", + "metadata": {}, + "outputs": [], + "source": [ + "# reorder the Antibiotics for ASIST\n", + "clsi_ab=['Amikacin','Tobramycin','Gentamycin','Imipenem','Meropenem','Doripenem','Ciprofloxacin','Levofloxacin',\n", + " 'Piperacillin/tazobactam','Ticarcillin/clavulanicacid','Cefotaxime','Ceftriaxone','Ceftazidime','Cefepime',\n", + " 'Trimethoprim/sulfamethoxazole','Ampicillin/sulbactam','Colistin','Polymyxinb','Tetracycline','Doxicycline ',\n", + " 'Minocycline']\n", + "result_selected=result_table.filter(clsi_ab)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "e0d983b9", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(9, 12)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result_selected.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "04376d0a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(9, 12)" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result_table.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "1b0a4d77", + "metadata": {}, + "outputs": [], + "source": [ + "result_selected.insert(0,'Resistance_phenotype','')" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "d36dcdab", + "metadata": {}, + "outputs": [], + "source": [ + "result_selected.to_csv(output_table,na_rep='NA')" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "5c162c07", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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AntibioticsResistance_phenotypeImipenemMeropenemCiprofloxacinPiperacillin/ tazobactamTicarcillin/clavulanic acidCeftriaxoneCeftazidimeCefepimeTrimethoprim/ sulfamethoxazoleAmpicillin/ sulbactamColistinPolymyxin B
Strain name
Acinetobacter baumannii A85NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNSusceptibleNaN
Acinetobacter baumannii AB307-0294SusceptibleSusceptibleNaNStrain could not classifiedNaNIntermediateNaNSusceptibleNaNStrain could not classifiedNaNNaN
Acinetobacter baumannii AB5075-UWNaNNaNResistantNaNNaNNaNResistantResistantNaNNaNNaNNaN
Acinetobacter baumannii DU202NaNNaNNaNStrain could not classifiedResistantNaNNaNNaNResistantStrain could not classifiedStrain could not classifiedNaN
Acinetobacter baumannii ORAB01NaNNaNNaNIntermediateNaNNaNNaNNaNNaNNaNNaNNaN
Acinetobacter baumannii strain FDA-CDC-AR_0305NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNSusceptible
Acinetobacter baumannii strain FDA-CDC-AR_0306NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNSusceptible
Acinetobacter baumannii strain FDA-CDC-AR_0307NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNResistant
Acinetobacter baumannii strain FDA-CDC-AR_0308NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNResistant
\n", + "
" + ], + "text/plain": [ + "Antibiotics Resistance_phenotype \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 \n", + "Acinetobacter baumannii AB307-0294 \n", + "Acinetobacter baumannii AB5075-UW \n", + "Acinetobacter baumannii DU202 \n", + "Acinetobacter baumannii ORAB01 \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 \n", + "\n", + "Antibiotics Imipenem Meropenem \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN NaN \n", + "Acinetobacter baumannii AB307-0294 Susceptible Susceptible \n", + "Acinetobacter baumannii AB5075-UW NaN NaN \n", + "Acinetobacter baumannii DU202 NaN NaN \n", + "Acinetobacter baumannii ORAB01 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN NaN \n", + "\n", + "Antibiotics Ciprofloxacin \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 NaN \n", + "Acinetobacter baumannii AB5075-UW Resistant \n", + "Acinetobacter baumannii DU202 NaN \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Piperacillin/ tazobactam \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 Strain could not classified \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 Strain could not classified \n", + "Acinetobacter baumannii ORAB01 Intermediate \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Ticarcillin/clavulanic acid \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 NaN \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 Resistant \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Ceftriaxone Ceftazidime \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN NaN \n", + "Acinetobacter baumannii AB307-0294 Intermediate NaN \n", + "Acinetobacter baumannii AB5075-UW NaN Resistant \n", + "Acinetobacter baumannii DU202 NaN NaN \n", + "Acinetobacter baumannii ORAB01 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN NaN \n", + "\n", + "Antibiotics Cefepime \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 Susceptible \n", + "Acinetobacter baumannii AB5075-UW Resistant \n", + "Acinetobacter baumannii DU202 NaN \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Trimethoprim/ sulfamethoxazole \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 NaN \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 Resistant \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Ampicillin/ sulbactam \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 Strain could not classified \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 Strain could not classified \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Colistin \\\n", + "Strain name \n", + "Acinetobacter baumannii A85 Susceptible \n", + "Acinetobacter baumannii AB307-0294 NaN \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 Strain could not classified \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 NaN \n", + "\n", + "Antibiotics Polymyxin B \n", + "Strain name \n", + "Acinetobacter baumannii A85 NaN \n", + "Acinetobacter baumannii AB307-0294 NaN \n", + "Acinetobacter baumannii AB5075-UW NaN \n", + "Acinetobacter baumannii DU202 NaN \n", + "Acinetobacter baumannii ORAB01 NaN \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0305 Susceptible \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0306 Susceptible \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0307 Resistant \n", + "Acinetobacter baumannii strain FDA-CDC-AR_0308 Resistant " + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#rename headers\n", + "result_selected.rename(columns = {'Ticarcillin/clavulanicacid':'Ticarcillin/clavulanic acid','Piperacillin/tazobactam':'Piperacillin/ tazobactam','Trimethoprim/sulfamethoxazole': 'Trimethoprim/ sulfamethoxazole','Ampicillin/sulbactam':'Ampicillin/ sulbactam', 'Polymyxinb': 'Polymyxin B'} )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "00cd53d4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "475401df", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.1" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff -r 306236ec0511 -r 683299422575 clsi_profile_type2_linux.ipynb --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/clsi_profile_type2_linux.ipynb Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,1040 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 37, + "id": "9aa0a6f7", + "metadata": {}, + "outputs": [], + "source": [ + "# ASIST module2 | map AST result to the CLSI breakporints with combination antibiotics\n", + "# By rakesh4osdd@gmail.com, 06-Jun-2021\n", + "import pandas as pd\n", + "import re\n", + "import sys" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "9af8387e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.2.4 2.2.1\n" + ] + } + ], + "source": [ + "#print(pd.__version__, re.__version__)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "73d0783c", + "metadata": {}, + "outputs": [], + "source": [ + "# compare two MIC value strings\n", + "def check_mic(mic1,mic2,mic_type):\n", + " #print(mic1,mic2,mic_type)\n", + " try:\n", + " if '/' in mic1:\n", + " m1a = mic1.split('/')[0]\n", + " m1b = mic1.split('/')[1]\n", + " if float(m1a)==0 or float(m1b)==0:\n", + " strain_type='Strain could not be classified'\n", + " return(strain_type) \n", + " elif '/' in mic2:\n", + " m1a = mic1\n", + " if float(m1a)==0:\n", + " strain_type='Strain could not be classified'\n", + " return(strain_type) \n", + " m1b = '1'\n", + " elif float(mic1)==0:\n", + " strain_type='Strain could not be classified'\n", + " return(strain_type)\n", + " else:\n", + " m1a = mic1\n", + " \n", + " if '-' in mic2:\n", + " m2a = mic2.split('-')[0]\n", + " m2b = mic2.split('-')[1] \n", + " \n", + " except ValueError:\n", + " strain_type='Strain could not be classified' \n", + " return(strain_type)\n", + " try:\n", + " if '-' in mic2 and mic_type == 'i': # for intermediate only\n", + " if '/' in mic2:\n", + " m2a = mic2.split('-')[0].split('/')[0]\n", + " m2b = mic2.split('-')[0].split('/')[1]\n", + " m2aa = mic2.split('-')[1].split('/')[0]\n", + " m2bb = mic2.split('-')[1].split('/')[1]\n", + " if (float(m2aa)>=float(m1a)>=float(m2a) and float(m2bb)>=float(m1b)>=float(m2b)):\n", + " #print('intermediate')\n", + " m_type='Intermediate'\n", + " else:\n", + " #print('not define')\n", + " m_type='Strain could not be classified'\n", + " else:\n", + " m2a = mic2.split('-')[0]\n", + " m2b = mic2.split('-')[1] \n", + " if (float(m2b)>=float(m1a)>=float(m2a)):\n", + " #print('intermediate')\n", + " m_type='Intermediate'\n", + " else:\n", + " #print('not define')\n", + " m_type='Strain could not be classified' \n", + " #print (m1a,m1b,m2a,m2b,m2aa,m2bb)\n", + " elif '/' in mic2:\n", + " m2a = mic2.split('/')[0]\n", + " m2b = mic2.split('/')[1]\n", + " #print(m1a,m1b,m2a,m2b,mic_type)\n", + " if (mic_type=='s' and (float(m1a)<=float(m2a) and float(m1b)<=float(m2b))):\n", + " m_type='Susceptible'\n", + " elif (mic_type=='r' and (float(m1a)>=float(m2a) and float(m1b)>=float(m2b))):\n", + " m_type='Resistant'\n", + " elif (mic_type=='i' and (float(m1a)==float(m2a) and float(m1b)==float(m2b))):\n", + " m_type='Intermediate'\n", + " else:\n", + " m_type='Strain could not be classified'\n", + " elif '-' in mic2:\n", + " m_type='Strain could not be classified'\n", + " else:\n", + " m2a=mic2\n", + " if (mic_type=='s' and (float(m1a)<=float(m2a))):\n", + " m_type='Susceptible'\n", + " elif (mic_type=='r' and (float(m1a)>=float(m2a))):\n", + " m_type='Resistant'\n", + " elif (mic_type=='i' and (float(m1a)==float(m2a))):\n", + " m_type='Intermediate'\n", + " else:\n", + " m_type='Strain could not be classified-1' \n", + " except IndexError:\n", + " strain_type='Strain could not be classified-2' \n", + " return(strain_type)\n", + " \n", + " return(m_type)\n", + "\n", + "#check_mic('65','32-64','i')" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "4d2ab1b1", + "metadata": {}, + "outputs": [], + "source": [ + "# compare MIC value in pandas list\n", + "def sus_res_int(mic):\n", + " #print(mic)\n", + " o_mic = mic[0].replace(' ', '')\n", + " s_mic = mic[1].replace(' ', '')\n", + " r_mic = mic[2].replace(' ', '')\n", + " i_mic = mic[3].replace(' ', '')\n", + " try:\n", + " if check_mic(o_mic,s_mic,'s')=='Susceptible':\n", + " strain_type='Susceptible'\n", + " elif check_mic(o_mic,r_mic,'r')=='Resistant':\n", + " strain_type='Resistant'\n", + " elif check_mic(o_mic,i_mic,'i')=='Intermediate':\n", + " strain_type='Intermediate' \n", + " else:\n", + " strain_type='Strain could not be classified'\n", + " except ValueError:\n", + " strain_type='Strain could not be classified' \n", + " return(strain_type)\n", + "\n", + "#mic=['128','16/4','128/4','32/4-64/4']\n", + "#sus_res_int(mic)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "0e22ef0d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'# for input argument\\ninput_user = sys.argv[1]\\ninput_clsi = sys.argv[2]\\noutput_table = sys.argv[3]'" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# for input argument\n", + "input_user = sys.argv[1]\n", + "input_clsi = sys.argv[2]\n", + "output_table = sys.argv[3]" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "21d5fe63", + "metadata": {}, + "outputs": [], + "source": [ + "'''input_user='input2.csv'\n", + "input_clsi='clsi.csv'\n", + "output_profile=input_user+'_profile.csv'\n", + "output_table=input_user+'_table.csv''''" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "1e64b025", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Strain nameAntibioticsMIC
0Acinetobacter baumannii A85Colistin0.1
1Acinetobacter baumannii A85Netilmicin1
2Acinetobacter baumannii AB307-0294Ampicillin0
3Acinetobacter baumannii AB307-0294Ampicillin/sulbactammg/L
4Acinetobacter baumannii AB307-0294piperacillin/tazobactam0
5Acinetobacter baumannii AB307-0294Cefazolin64
6Acinetobacter baumannii AB307-0294Ceftriaxone16
7Acinetobacter baumannii AB307-0294Cefepime8
8Acinetobacter baumannii AB307-0294Meropenem0.25
9Acinetobacter baumannii AB307-0294Imipenem1
10Acinetobacter baumannii AB307-0294Tigecycline0.5
11Acinetobacter baumannii AB5075-UWCeftazidime>128
12Acinetobacter baumannii AB5075-UWCefepime>256
13Acinetobacter baumannii AB5075-UWCiprofloxacin>32
14Acinetobacter baumannii DU202colistin
15Acinetobacter baumannii DU202Ampicillin/sulbactam>=0.3 mg/L
16Acinetobacter baumannii DU202ticarcillin/clavulanic acid>=128/2
17Acinetobacter baumannii DU202piperacillin/tazobactamNA
18Acinetobacter baumannii DU202trimethoprim/sulfamethoxazole8/152
19Acinetobacter baumannii ORAB01piperacillin/tazobactam>64/4
20Acinetobacter baumannii strain MRSN7100amoxicillin/clavulanic acid16/8
21Acinetobacter baumannii strain MRSN7168amoxicillin/clavulanic acid16/8
22Acinetobacter baumannii strain MRSN7336amoxicillin/clavulanic acid16/8
23Acinetobacter baumannii strain MRSN7834amoxicillin/clavulanic acid16/8
24Acinetobacter baumannii strain FDA-CDC-AR_0305polymyxin B1
25Acinetobacter baumannii strain FDA-CDC-AR_0306polymyxin B1
26Acinetobacter baumannii strain FDA-CDC-AR_0307polymyxin B8
27Acinetobacter baumannii strain FDA-CDC-AR_0308polymyxin B4
\n", + "
" + ], + "text/plain": [ + " Strain name \\\n", + "0 Acinetobacter baumannii A85 \n", + "1 Acinetobacter baumannii A85 \n", + "2 Acinetobacter baumannii AB307-0294 \n", + "3 Acinetobacter baumannii AB307-0294 \n", + "4 Acinetobacter baumannii AB307-0294 \n", + "5 Acinetobacter baumannii AB307-0294 \n", + "6 Acinetobacter baumannii AB307-0294 \n", + "7 Acinetobacter baumannii AB307-0294 \n", + "8 Acinetobacter baumannii AB307-0294 \n", + "9 Acinetobacter baumannii AB307-0294 \n", + "10 Acinetobacter baumannii AB307-0294 \n", + "11 Acinetobacter baumannii AB5075-UW \n", + "12 Acinetobacter baumannii AB5075-UW \n", + "13 Acinetobacter baumannii AB5075-UW \n", + "14 Acinetobacter baumannii DU202 \n", + "15 Acinetobacter baumannii DU202 \n", + "16 Acinetobacter baumannii DU202 \n", + "17 Acinetobacter baumannii DU202 \n", + "18 Acinetobacter baumannii DU202 \n", + "19 Acinetobacter baumannii ORAB01 \n", + "20 Acinetobacter baumannii strain MRSN7100 \n", + "21 Acinetobacter baumannii strain MRSN7168 \n", + "22 Acinetobacter baumannii strain MRSN7336 \n", + "23 Acinetobacter baumannii strain MRSN7834 \n", + "24 Acinetobacter baumannii strain FDA-CDC-AR_0305 \n", + "25 Acinetobacter baumannii strain FDA-CDC-AR_0306 \n", + "26 Acinetobacter baumannii strain FDA-CDC-AR_0307 \n", + "27 Acinetobacter baumannii strain FDA-CDC-AR_0308 \n", + "\n", + " Antibiotics MIC \n", + "0 Colistin 0.1 \n", + "1 Netilmicin 1 \n", + "2 Ampicillin 0 \n", + "3 Ampicillin/sulbactam mg/L \n", + "4 piperacillin/tazobactam 0 \n", + "5 Cefazolin 64 \n", + "6 Ceftriaxone 16 \n", + "7 Cefepime 8 \n", + "8 Meropenem 0.25 \n", + "9 Imipenem 1 \n", + "10 Tigecycline 0.5 \n", + "11 Ceftazidime >128 \n", + "12 Cefepime >256 \n", + "13 Ciprofloxacin >32 \n", + "14 colistin \n", + "15 Ampicillin/sulbactam >=0.3 mg/L \n", + "16 ticarcillin/clavulanic acid >=128/2 \n", + "17 piperacillin/tazobactam NA \n", + "18 trimethoprim/sulfamethoxazole 8/152 \n", + "19 piperacillin/tazobactam >64/4 \n", + "20 amoxicillin/clavulanic acid 16/8 \n", + "21 amoxicillin/clavulanic acid 16/8 \n", + "22 amoxicillin/clavulanic acid 16/8 \n", + "23 amoxicillin/clavulanic acid 16/8 \n", + "24 polymyxin B 1 \n", + "25 polymyxin B 1 \n", + "26 polymyxin B 8 \n", + "27 polymyxin B 4 " + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# read user AST data with selected 3 columns\n", + "strain_mic=pd.read_csv(input_user, sep=',', usecols =['Strain name', 'Antibiotics', 'MIC'],na_filter=False)\n", + "#strain_mic" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "0d30ddc3", + "metadata": {}, + "outputs": [], + "source": [ + "clsi_bp=pd.read_csv(input_clsi,sep=',')\n", + "\n", + "#clsi_bp[clsi_bp[['Antibiotics', 'Susceptible']].duplicated()].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "a818676d", + "metadata": {}, + "outputs": [], + "source": [ + "#clsi_bp\n", + "#strain_mic" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "c6b4c59b", + "metadata": {}, + "outputs": [], + "source": [ + "# convert MIC to numbers sMIC, rMIC\n", + "clsi_bp['s_mic'] =clsi_bp[['Susceptible']].applymap(lambda x: (re.sub(r'[^0-9.\\/-]', '', x)))\n", + "clsi_bp['r_mic'] =clsi_bp[['Resistant']].applymap(lambda x: (re.sub(r'[^0-9.\\/-]', '', x)))\n", + "clsi_bp['i_mic'] = clsi_bp[['Intermediate']].applymap(lambda x: (re.sub(r'[^0-9.\\/-]', '', x)))" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "d0171f94", + "metadata": {}, + "outputs": [], + "source": [ + "#clsi_bp['i_mic'] = clsi_bp[['Intermediate']].applymap(lambda x: (re.sub(r'[^0-9.\\/-]', '', x)))" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "fe45b2dd", + "metadata": {}, + "outputs": [], + "source": [ + "# Read only numbers in MIC values\n", + "#try:\n", + "strain_mic['o_mic']=strain_mic[['MIC']].applymap(lambda x: (re.sub(r'[^0-9.\\/]','', x)))\n", + "#except TypeError:\n", + "# print('Waring: Error in MIC value')" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "ddbbe4d9", + "metadata": {}, + "outputs": [], + "source": [ + "#strain_mic" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "640508f1", + "metadata": {}, + "outputs": [], + "source": [ + "# capitalize each Antibiotic Name for comparision with removing whitespace\n", + "strain_mic['Strain name']=strain_mic['Strain name'].str.capitalize().str.replace(\" \",\"\")\n", + "strain_mic['Antibiotics']=strain_mic['Antibiotics'].str.capitalize().str.replace(\" \",\"\")\n", + "\n", + "clsi_bp['Antibiotics']=clsi_bp['Antibiotics'].str.capitalize().str.replace(\" \",\"\")" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "b87426f4", + "metadata": {}, + "outputs": [], + "source": [ + "#find duplicate values in input files\n", + "dups=strain_mic[strain_mic[['Strain name', 'Antibiotics']].duplicated(keep=False)]\n", + "if dups.shape[0] != 0:\n", + " print ('Please provide a single MIC value in input file for given duplicates combination of \\'Strain name and Antibiotics\\' to use the tool:-\\n',dups)\n", + " #exit()\n", + "else:\n", + " #compare CLSI Antibiotics only\n", + " #result=pd.merge(strain_mic, clsi_bp, on='Antibiotics',how='inner', indicator=True)[['Strain name','Antibiotics', 'MIC', 'o_mic', 's_mic', 'r_mic','_merge']]\n", + " try:\n", + " result=pd.merge(strain_mic, clsi_bp, on='Antibiotics',how='inner')[['Strain name','Antibiotics', 'MIC', 'o_mic', 's_mic', 'r_mic','i_mic']]\n", + " except KeyError:\n", + " print('Waring: Error in input Values')" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "91bfc94d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Strain nameAntibioticsMICo_mics_micr_mici_mic
0Acinetobacterbaumanniia85Colistin0.10.1-42
1Acinetobacterbaumanniidu202Colistin-42
2Acinetobacterbaumanniia85Netilmicin1183216
3Acinetobacterbaumanniiab307-0294Ampicillin/sulbactammg/L/8/432/1616/8
4Acinetobacterbaumanniidu202Ampicillin/sulbactam>=0.3 mg/L0.3/8/432/1616/8
5Acinetobacterbaumanniiab307-0294Piperacillin/tazobactam0016/4128/432/4-64/4
6Acinetobacterbaumanniidu202Piperacillin/tazobactamNA16/4128/432/4-64/4
7Acinetobacterbaumanniiorab01Piperacillin/tazobactam>64/464/416/4128/432/4-64/4
8Acinetobacterbaumanniiab307-0294Ceftriaxone161686416-32
9Acinetobacterbaumanniiab307-0294Cefepime8883216
10Acinetobacterbaumanniiab5075-uwCefepime>25625683216
11Acinetobacterbaumanniiab307-0294Meropenem0.250.25284
12Acinetobacterbaumanniiab307-0294Imipenem11284
13Acinetobacterbaumanniiab5075-uwCeftazidime>12812883216
14Acinetobacterbaumanniiab5075-uwCiprofloxacin>3232142
15Acinetobacterbaumanniidu202Ticarcillin/clavulanicacid>=128/2128/216/2128/232/2-64/2
16Acinetobacterbaumanniidu202Trimethoprim/sulfamethoxazole8/1528/1522/384/76-
17Acinetobacterbaumanniistrainfda-cdc-ar_0305Polymyxinb11-42
18Acinetobacterbaumanniistrainfda-cdc-ar_0306Polymyxinb11-42
19Acinetobacterbaumanniistrainfda-cdc-ar_0307Polymyxinb88-42
20Acinetobacterbaumanniistrainfda-cdc-ar_0308Polymyxinb44-42
\n", + "
" + ], + "text/plain": [ + " Strain name \\\n", + "0 Acinetobacterbaumanniia85 \n", + "1 Acinetobacterbaumanniidu202 \n", + "2 Acinetobacterbaumanniia85 \n", + "3 Acinetobacterbaumanniiab307-0294 \n", + "4 Acinetobacterbaumanniidu202 \n", + "5 Acinetobacterbaumanniiab307-0294 \n", + "6 Acinetobacterbaumanniidu202 \n", + "7 Acinetobacterbaumanniiorab01 \n", + "8 Acinetobacterbaumanniiab307-0294 \n", + "9 Acinetobacterbaumanniiab307-0294 \n", + "10 Acinetobacterbaumanniiab5075-uw \n", + "11 Acinetobacterbaumanniiab307-0294 \n", + "12 Acinetobacterbaumanniiab307-0294 \n", + "13 Acinetobacterbaumanniiab5075-uw \n", + "14 Acinetobacterbaumanniiab5075-uw \n", + "15 Acinetobacterbaumanniidu202 \n", + "16 Acinetobacterbaumanniidu202 \n", + "17 Acinetobacterbaumanniistrainfda-cdc-ar_0305 \n", + "18 Acinetobacterbaumanniistrainfda-cdc-ar_0306 \n", + "19 Acinetobacterbaumanniistrainfda-cdc-ar_0307 \n", + "20 Acinetobacterbaumanniistrainfda-cdc-ar_0308 \n", + "\n", + " Antibiotics MIC o_mic s_mic r_mic i_mic \n", + "0 Colistin 0.1 0.1 - 4 2 \n", + "1 Colistin - 4 2 \n", + "2 Netilmicin 1 1 8 32 16 \n", + "3 Ampicillin/sulbactam mg/L / 8/4 32/16 16/8 \n", + "4 Ampicillin/sulbactam >=0.3 mg/L 0.3/ 8/4 32/16 16/8 \n", + "5 Piperacillin/tazobactam 0 0 16/4 128/4 32/4-64/4 \n", + "6 Piperacillin/tazobactam NA 16/4 128/4 32/4-64/4 \n", + "7 Piperacillin/tazobactam >64/4 64/4 16/4 128/4 32/4-64/4 \n", + "8 Ceftriaxone 16 16 8 64 16-32 \n", + "9 Cefepime 8 8 8 32 16 \n", + "10 Cefepime >256 256 8 32 16 \n", + "11 Meropenem 0.25 0.25 2 8 4 \n", + "12 Imipenem 1 1 2 8 4 \n", + "13 Ceftazidime >128 128 8 32 16 \n", + "14 Ciprofloxacin >32 32 1 4 2 \n", + "15 Ticarcillin/clavulanicacid >=128/2 128/2 16/2 128/2 32/2-64/2 \n", + "16 Trimethoprim/sulfamethoxazole 8/152 8/152 2/38 4/76 - \n", + "17 Polymyxinb 1 1 - 4 2 \n", + "18 Polymyxinb 1 1 - 4 2 \n", + "19 Polymyxinb 8 8 - 4 2 \n", + "20 Polymyxinb 4 4 - 4 2 " + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#result" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "b171f205", + "metadata": {}, + "outputs": [], + "source": [ + "#compare MIC values and assign Susceptible and Resistant to Strain\n", + "#try:\n", + "result[['CLSI_profile']] = result[['o_mic','s_mic','r_mic','i_mic']].apply(sus_res_int,axis = 1)\n", + "#except ValueError:\n", + "# print('Waring: Error in input MIC value')" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "3336fd92", + "metadata": {}, + "outputs": [], + "source": [ + "#result" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "f0dacfd1", + "metadata": {}, + "outputs": [], + "source": [ + "#result[['Strain name', 'Antibiotics', 'MIC','s_mic','r_mic','CLSI_profile']].to_csv(output_profile,sep=',', index=False, encoding='utf-8-sig')" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "id": "3d8d03f7", + "metadata": {}, + "outputs": [], + "source": [ + "#create a pivot table for ASIST\n", + "table=result[['Strain name', 'Antibiotics','CLSI_profile']].drop_duplicates()\n", + "result_table=pd.pivot_table(table, values ='CLSI_profile', index =['Strain name'],columns =['Antibiotics'], aggfunc = lambda x: ' '.join(x))" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "7d7223a3", + "metadata": {}, + "outputs": [], + "source": [ + "#result_table" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "id": "8a41b2ef", + "metadata": {}, + "outputs": [], + "source": [ + "#result_table.to_csv(output_table,na_rep='NA')" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "id": "8c9e5f87", + "metadata": {}, + "outputs": [], + "source": [ + "# reorder the Antibiotics for ASIST\n", + "clsi_ab=['Amikacin','Tobramycin','Gentamycin','Netilmicin','Imipenem','Meropenem','Doripenem','Ciprofloxacin','Levofloxacin',\n", + " 'Piperacillin/tazobactam','Ticarcillin/clavulanicacid','Cefotaxime','Ceftriaxone','Ceftazidime','Cefepime',\n", + " 'Trimethoprim/sulfamethoxazole','Ampicillin/sulbactam','Colistin','Polymyxinb','Tetracycline','Doxicycline ',\n", + " 'Minocycline']\n", + "result_selected=result_table.filter(clsi_ab)" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "cdf43afb", + "metadata": {}, + "outputs": [], + "source": [ + "#print(result_selected.shape, result_table.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "id": "c4c4df30", + "metadata": {}, + "outputs": [], + "source": [ + "#result_selected.insert(0,'Resistance_phenotype','')" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "id": "9adb2703", + "metadata": {}, + "outputs": [], + "source": [ + "#rename headers\n", + "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'} )" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "id": "50e6cf5f", + "metadata": {}, + "outputs": [], + "source": [ + "#result_selected" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "id": "2833671c", + "metadata": {}, + "outputs": [], + "source": [ + "result_selected.to_csv(output_table,na_rep='NA')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff -r 306236ec0511 -r 683299422575 input.csv --- a/input.csv Fri Jun 11 13:20:08 2021 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,31 +0,0 @@ -id,genome Ids,Strain name,Antibiotics,Resistance_profile,sign,MIC,unit -470,CP021782.1,Acinetobacter baumannii A85,Colistin,Susceptible ,NA,0.1,mg/L -470,CP021782.1,Acinetobacter baumannii A85,Colistin,Susceptible ,NA,1,mg/L -470,CP021782.1,Acinetobacter baumannii A85,Colistin,Susceptible ,NA,2,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Ampicillin,resistant,>=,0,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Ampicillin/sulbactam,susceptible,<=,mg/L,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,piperacillin/tazobactam,susceptible,<=,0,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Cefazolin,resistant,>=,64,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Ceftriaxone,susceptible,==,16,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Cefepime,susceptible,==,8,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Meropenem,susceptible,<=,0.25,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Imipenem,susceptible,<=,1,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Tigecycline,susceptible,<=,0.5,mg/L -470,CP008706.1,Acinetobacter baumannii AB5075-UW,Ceftazidime,Resistant,NA,>128,mg/L -470,CP008706.1,Acinetobacter baumannii AB5075-UW,Cefepime,Resistant,NA,>256,mg/L -470,CP008706.1,Acinetobacter baumannii AB5075-UW,Ciprofloxacin,Resistant,NA,>32,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,colistin ,Susceptible,NA,,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,trimethoprim/sulfamethoxazole,Resistant,NA,8/152,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,Ampicillin/sulbactam,Resistant,NA,>=0.3 mg/L,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,ticarcillin/clavulanic acid,Resistant,NA,>=128/2,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,piperacillin/tazobactam ,Resistant,NA,NA,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,trimethoprim/sulfamethoxazole,Resistant,NA,8/152,mg/L -470,CP015483.1,Acinetobacter baumannii ORAB01,piperacillin/tazobactam,Resistant,NA,>64/4,mg/L -470,470.7601,Acinetobacter baumannii strain MRSN7100,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L -470,470.7651,Acinetobacter baumannii strain MRSN7168,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L -470,470.7764,Acinetobacter baumannii strain MRSN7336,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L -470,470.8071,Acinetobacter baumannii strain MRSN7834,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L -470,470.7405,Acinetobacter baumannii strain FDA-CDC-AR_0305,polymyxin B,Susceptible,==,1,mg/L -470,470.7406,Acinetobacter baumannii strain FDA-CDC-AR_0306,polymyxin B,Susceptible,==,1,mg/L -470,470.7407,Acinetobacter baumannii strain FDA-CDC-AR_0307,polymyxin B,Resistant,==,8,mg/L -470,470.7408,Acinetobacter baumannii strain FDA-CDC-AR_0308,polymyxin B,Resistant,==,4,mg/L diff -r 306236ec0511 -r 683299422575 input.csv_table.csv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/input.csv_table.csv Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,10 @@ +Strain name,Resistance_phenotype,Imipenem,Meropenem,Ciprofloxacin,Piperacillin/ tazobactam,Ticarcillin/clavulanic acid,Ceftriaxone,Ceftazidime,Cefepime,Trimethoprim/ sulfamethoxazole,Ampicillin/ sulbactam,Colistin,Polymyxin B +Acinetobacter baumannii A85,,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,Strain could not be classified Intermediate,NA +Acinetobacter baumannii AB307-0294,,Susceptible,Susceptible,NA,Strain could not be classified,NA,Intermediate,NA,Susceptible,NA,Strain could not be classified,NA,NA +Acinetobacter baumannii AB5075-UW,,NA,NA,Resistant,NA,NA,NA,Resistant,Resistant,NA,NA,NA,NA +Acinetobacter baumannii DU202,,NA,NA,NA,Strain could not be classified,Resistant,NA,NA,NA,Resistant,Strain could not be classified,Strain could not be classified,NA +Acinetobacter baumannii ORAB01,,NA,NA,NA,Intermediate,NA,NA,NA,NA,NA,NA,NA,NA +Acinetobacter baumannii strain FDA-CDC-AR_0305,,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,Strain could not be classified +Acinetobacter baumannii strain FDA-CDC-AR_0306,,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,Strain could not be classified +Acinetobacter baumannii strain FDA-CDC-AR_0307,,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,Resistant +Acinetobacter baumannii strain FDA-CDC-AR_0308,,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,Resistant diff -r 306236ec0511 -r 683299422575 suite_config.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/suite_config.xml Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,9 @@ + + This suite contains clsi_profile and asist files and wrappers for Galaxy + + MIC profile using CLSI MIC breakpoints + + + Antimicrobial Susceptibility standards based phenotypes + + diff -r 306236ec0511 -r 683299422575 test-data/asist_input.csv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/asist_input.csv Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,5 @@ +Strain name,Resistance_phenotype,Amikacin,Tobramycin,Gentamycin,Imipenem,Meropenam,Doripenem,Ciprofloxacin,Levofloxacin,Piperacillin/tazobactam,Ticarcillin/clavulanic acid,Cefotaxime,Ceftriaxone,Ceftazidime,Cefepime,Trimethoprim/sulfamethoxazole,Ampicillin/sulbactam,Colistin,polymyxin B,Tetracycline,Doxicycline ,Minocycline +Strain name,Resistance_phenotype,Aminoglycoside,Aminoglycoside,Aminoglycoside,Beta-lactams-Carbapenems,Beta-lactams-Carbapenems,Carbapenem ,Fluoroquinolone,Fluoroquinolone,Beta-lactam inhibitor,Beta-lactam inhibitor,Cephalosporin,Cephalosporin,Cephalosporin,Cephalosporin,Sulfonamides,Penicillins/beta-lactamase,Polymyxins,Polymyxins,Tetracycline,Tetracycline,Tetracycline +Acinetobacter baumannii strain FDA-CDC-AR_0288,,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant +Acinetobacter baumannii strain FDA-CDC-AR_0303,,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,NA +Acinetobacter baumannii strain FDA-CDC-AR_0304,,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant diff -r 306236ec0511 -r 683299422575 test-data/asist_output.csv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/asist_output.csv Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,5 @@ +Strain name,Strain phenotype,Resistance_phenotype,Amikacin,Tobramycin,Gentamycin,Imipenem,Meropenam,Doripenem,Ciprofloxacin,Levofloxacin,Piperacillin/ tazobactam,Ticarcillin/ clavulanic acid,Cefotaxime,Ceftriaxone,Ceftazidime,Cefepime,Trimethoprim/ sulfamethoxazole,Ampicillin/ sulbactam,Colistin,Polymyxin B,Tetracycline,Doxicycline,Minocycline +Strain name,Strain could not be classified,Resistance_phenotype,Aminoglycoside,Aminoglycoside,Aminoglycoside,Beta-lactams-Carbapenems,Beta-lactams-Carbapenems,Carbapenem ,Fluoroquinolone,Fluoroquinolone,Beta-lactam inhibitor,Beta-lactam inhibitor,Cephalosporin,Cephalosporin,Cephalosporin,Cephalosporin,Sulfonamides,Penicillins/beta-lactamase,Polymyxins,Polymyxins,Tetracycline,Tetracycline,Tetracycline +Acinetobacter baumannii strain FDA-CDC-AR_0288,Possible TDR,,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant +Acinetobacter baumannii strain FDA-CDC-AR_0303,Possible TDR,,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,NA +Acinetobacter baumannii strain FDA-CDC-AR_0304,Possible TDR,,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant diff -r 306236ec0511 -r 683299422575 test-data/input.csv --- a/test-data/input.csv Fri Jun 11 13:20:08 2021 +0000 +++ b/test-data/input.csv Tue Jun 29 05:20:41 2021 +0000 @@ -1,31 +1,31 @@ -id,genome Ids,Strain name,Antibiotics,Resistance_profile,sign,MIC,unit -470,CP021782.1,Acinetobacter baumannii A85,Colistin,Susceptible ,NA,0.1,mg/L -470,CP021782.1,Acinetobacter baumannii A85,Colistin,Susceptible ,NA,1,mg/L -470,CP021782.1,Acinetobacter baumannii A85,Colistin,Susceptible ,NA,2,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Ampicillin,resistant,>=,0,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Ampicillin/sulbactam,susceptible,<=,mg/L,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,piperacillin/tazobactam,susceptible,<=,0,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Cefazolin,resistant,>=,64,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Ceftriaxone,susceptible,==,16,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Cefepime,susceptible,==,8,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Meropenem,susceptible,<=,0.25,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Imipenem,susceptible,<=,1,mg/L -470,CP001172.2,Acinetobacter baumannii AB307-0294,Tigecycline,susceptible,<=,0.5,mg/L -470,CP008706.1,Acinetobacter baumannii AB5075-UW,Ceftazidime,Resistant,NA,>128,mg/L -470,CP008706.1,Acinetobacter baumannii AB5075-UW,Cefepime,Resistant,NA,>256,mg/L -470,CP008706.1,Acinetobacter baumannii AB5075-UW,Ciprofloxacin,Resistant,NA,>32,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,colistin ,Susceptible,NA,,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,trimethoprim/sulfamethoxazole,Resistant,NA,8/152,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,Ampicillin/sulbactam,Resistant,NA,>=0.3 mg/L,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,ticarcillin/clavulanic acid,Resistant,NA,>=128/2,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,piperacillin/tazobactam ,Resistant,NA,NA,mg/L -470,CP017152.1,Acinetobacter baumannii DU202,trimethoprim/sulfamethoxazole,Resistant,NA,8/152,mg/L -470,CP015483.1,Acinetobacter baumannii ORAB01,piperacillin/tazobactam,Resistant,NA,>64/4,mg/L -470,470.7601,Acinetobacter baumannii strain MRSN7100,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L -470,470.7651,Acinetobacter baumannii strain MRSN7168,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L -470,470.7764,Acinetobacter baumannii strain MRSN7336,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L -470,470.8071,Acinetobacter baumannii strain MRSN7834,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L -470,470.7405,Acinetobacter baumannii strain FDA-CDC-AR_0305,polymyxin B,Susceptible,==,1,mg/L -470,470.7406,Acinetobacter baumannii strain FDA-CDC-AR_0306,polymyxin B,Susceptible,==,1,mg/L -470,470.7407,Acinetobacter baumannii strain FDA-CDC-AR_0307,polymyxin B,Resistant,==,8,mg/L -470,470.7408,Acinetobacter baumannii strain FDA-CDC-AR_0308,polymyxin B,Resistant,==,4,mg/L +id,Strain name,Antibiotics,Resistance_profile,sign,MIC,unit +470,Acinetobacter baumannii A85,Colistin,Susceptible ,NA,0.1,mg/L +470,Acinetobacter baumannii A85,Colistin,Susceptible ,NA,1,mg/L +470,Acinetobacter baumannii A85,Colistin,Susceptible ,NA,2,mg/L +470,Acinetobacter baumannii AB307-0294,Ampicillin,resistant,>=,0,mg/L +470,Acinetobacter baumannii AB307-0294,Ampicillin/sulbactam,susceptible,<=,mg/L,mg/L +470,Acinetobacter baumannii AB307-0294,piperacillin/tazobactam,susceptible,<=,0,mg/L +470,Acinetobacter baumannii AB307-0294,Cefazolin,resistant,>=,64,mg/L +470,Acinetobacter baumannii AB307-0294,Ceftriaxone,susceptible,==,16,mg/L +470,Acinetobacter baumannii AB307-0294,Cefepime,susceptible,==,8,mg/L +470,Acinetobacter baumannii AB307-0294,Meropenem,susceptible,<=,0.25,mg/L +470,Acinetobacter baumannii AB307-0294,Imipenem,susceptible,<=,1,mg/L +470,Acinetobacter baumannii AB307-0294,Tigecycline,susceptible,<=,0.5,mg/L +470,Acinetobacter baumannii AB5075-UW,Ceftazidime,Resistant,NA,>128,mg/L +470,Acinetobacter baumannii AB5075-UW,Cefepime,Resistant,NA,>256,mg/L +470,Acinetobacter baumannii AB5075-UW,Ciprofloxacin,Resistant,NA,>32,mg/L +470,Acinetobacter baumannii DU202,colistin ,Susceptible,NA,,mg/L +470,Acinetobacter baumannii DU202,trimethoprim/sulfamethoxazole,Resistant,NA,8/152,mg/L +470,Acinetobacter baumannii DU202,Ampicillin/sulbactam,Resistant,NA,>=0.3 mg/L,mg/L +470,Acinetobacter baumannii DU202,ticarcillin/clavulanic acid,Resistant,NA,>=128/2,mg/L +470,Acinetobacter baumannii DU202,piperacillin/tazobactam ,Resistant,NA,NA,mg/L +470,Acinetobacter baumannii DU202,trimethoprim/sulfamethoxazole,Resistant,NA,8/152,mg/L +470,Acinetobacter baumannii ORAB01,piperacillin/tazobactam,Resistant,NA,>64/4,mg/L +470,Acinetobacter baumannii strain MRSN7100,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L +470,Acinetobacter baumannii strain MRSN7168,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L +470,Acinetobacter baumannii strain MRSN7336,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L +470,Acinetobacter baumannii strain MRSN7834,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L +470,Acinetobacter baumannii strain FDA-CDC-AR_0305,polymyxin B,Susceptible,==,1,mg/L +470,Acinetobacter baumannii strain FDA-CDC-AR_0306,polymyxin B,Susceptible,==,1,mg/L +470,Acinetobacter baumannii strain FDA-CDC-AR_0307,polymyxin B,Resistant,==,8,mg/L +470,Acinetobacter baumannii strain FDA-CDC-AR_0308,polymyxin B,Resistant,==,4,mg/L diff -r 306236ec0511 -r 683299422575 test-data/input2.csv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/input2.csv Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,29 @@ +id,genome Ids,Strain name,Antibiotics,Resistance_profile,sign,MIC,unit +470,CP021782.1,Acinetobacter baumannii A85,Colistin,Susceptible ,NA,0.1,mg/L +470,CP021782.1,Acinetobacter baumannii A85,Netilmicin,Susceptible ,NA,1,mg/L +470,CP001172.2,Acinetobacter baumannii AB307-0294,Ampicillin,resistant,>=,0,mg/L +470,CP001172.2,Acinetobacter baumannii AB307-0294,Ampicillin/sulbactam,susceptible,<=,mg/L,mg/L +470,CP001172.2,Acinetobacter baumannii AB307-0294,piperacillin/tazobactam,susceptible,<=,0,mg/L +470,CP001172.2,Acinetobacter baumannii AB307-0294,Cefazolin,resistant,>=,64,mg/L +470,CP001172.2,Acinetobacter baumannii AB307-0294,Ceftriaxone,susceptible,==,16,mg/L +470,CP001172.2,Acinetobacter baumannii AB307-0294,Cefepime,susceptible,==,8,mg/L +470,CP001172.2,Acinetobacter baumannii AB307-0294,Meropenem,susceptible,<=,0.25,mg/L +470,CP001172.2,Acinetobacter baumannii AB307-0294,Imipenem,susceptible,<=,1,mg/L +470,CP001172.2,Acinetobacter baumannii AB307-0294,Tigecycline,susceptible,<=,0.5,mg/L +470,CP008706.1,Acinetobacter baumannii AB5075-UW,Ceftazidime,Resistant,NA,>128,mg/L +470,CP008706.1,Acinetobacter baumannii AB5075-UW,Cefepime,Resistant,NA,>256,mg/L +470,CP008706.1,Acinetobacter baumannii AB5075-UW,Ciprofloxacin,Resistant,NA,>32,mg/L +470,CP017152.1,Acinetobacter baumannii DU202,colistin ,Susceptible,NA,,mg/L +470,CP017152.1,Acinetobacter baumannii DU202,Ampicillin/sulbactam,Resistant,NA,>=0.3 mg/L,mg/L +470,CP017152.1,Acinetobacter baumannii DU202,ticarcillin/clavulanic acid,Resistant,NA,>=128/2,mg/L +470,CP017152.1,Acinetobacter baumannii DU202,piperacillin/tazobactam ,Resistant,NA,NA,mg/L +470,CP017152.1,Acinetobacter baumannii DU202,trimethoprim/sulfamethoxazole,Resistant,NA,8/152,mg/L +470,CP015483.1,Acinetobacter baumannii ORAB01,piperacillin/tazobactam,Resistant,NA,>64/4,mg/L +470,470.7601,Acinetobacter baumannii strain MRSN7100,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L +470,470.7651,Acinetobacter baumannii strain MRSN7168,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L +470,470.7764,Acinetobacter baumannii strain MRSN7336,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L +470,470.8071,Acinetobacter baumannii strain MRSN7834,amoxicillin/clavulanic acid,Resistant,>, 16/8,mg/L +470,470.7405,Acinetobacter baumannii strain FDA-CDC-AR_0305,polymyxin B,Susceptible,==,1,mg/L +470,470.7406,Acinetobacter baumannii strain FDA-CDC-AR_0306,polymyxin B,Susceptible,==,1,mg/L +470,470.7407,Acinetobacter baumannii strain FDA-CDC-AR_0307,polymyxin B,Resistant,==,8,mg/L +470,470.7408,Acinetobacter baumannii strain FDA-CDC-AR_0308,polymyxin B,Resistant,==,4,mg/L diff -r 306236ec0511 -r 683299422575 tool_asist.sh --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool_asist.sh Tue Jun 29 05:20:41 2021 +0000 @@ -0,0 +1,13 @@ +#!/bin/bash + +planemo tool_init --id 'asist' --name 'ASIST' --version 1.0.1 \ + --description 'Antimicrobial Susceptibility standards based phenotypes' \ + --requirement 'pandas' \ + --example_command "\"${__tool_directory__}/asist_dynamic.py\" 'asist_input.csv' 'asist_output.csv'" \ + --example_input test-data/asist_input.csv \ + --example_output test-data/asist_output.csv \ + --test_case \ + --version_command 'python -c "import pandas; print(pandas.__version__)"' \ + --doi 'https://ab-openlab.csir.res.in/asist' + +planemo lint asist.xml diff -r 306236ec0511 -r 683299422575 tool_shed.sh --- a/tool_shed.sh Fri Jun 11 13:20:08 2021 +0000 +++ b/tool_shed.sh Tue Jun 29 05:20:41 2021 +0000 @@ -1,7 +1,5 @@ -planemo shed_init --name="clsi_profile" \ - --owner="rakesh4osdd" \ - --description="CLSI profile using MIC breakpoints" \ - --remote_repository_url="https://github.com/rakesh4osdd/clsi_profile/tree/master" \ - --homepage_url="https://github.com/rakesh4osdd/clsi_profile/tree/master" \ - --long_description="CLSI profile using MIC breakpoints" \ - # --category='' +#!/bin/bash +# After reviewing .shed.yml, this configuration file and relevant shed artifacts can be quickly linted using the following command. +planemo shed_lint --tools +#planemo shed_create --shed_target toolshed +planemo shed_update --check_diff --shed_target toolshed