updated kd.py to relfect a merging col for combining num params later
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parent
d44ab57f5a
commit
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3 changed files with 137 additions and 82 deletions
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@ -10,16 +10,7 @@ Created on Tue Aug 6 12:56:03 2019
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# concentrate on positions that have structural info?
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# FIXME: import dirs.py to get the basic dir paths available
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#%% load libraries
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import os, sys
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import pandas as pd
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#import numpy as np
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#from pandas.api.types import is_string_dtype
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#from pandas.api.types import is_numeric_dtype
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#========================================================
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#=======================================================================
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# TASK: extract ALL pncA_p. mutations from GWAS data
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# Input data file has the following format: each row = unique sample id
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# id,country,lineage,sublineage,drtype,pyrazinamide,dr_mutations_pyrazinamide,other_mutations_pyrazinamide...
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@ -38,46 +29,58 @@ import pandas as pd
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# 3) pnca_metadata.csv
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# 4) pnca_all_muts_msa.csv
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# 5) pnca_mutational_positons.csv
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#========================================================
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#=======================================================================
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#%% load libraries
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import os, sys
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import pandas as pd
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#import numpy as np
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#from pandas.api.types import is_string_dtype
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#from pandas.api.types import is_numeric_dtype
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#%% specify homedir as python doesn't recognise tilde
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homedir = os.path.expanduser('~')
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# my working dir
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# set working dir
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os.getcwd()
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os.chdir(homedir + '/git/LSHTM_analysis/meta_data_analysis')
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os.getcwd()
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# import aa dict
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from reference_dict import my_aa_dict #CHECK DIR STRUC THERE!
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#========================================================
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#=======================================================================
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#%% variable assignment: input and output paths & filenames
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drug = 'pyrazinamide'
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gene = 'pncA'
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gene_match = gene + '_p.'
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#==========
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# input dir
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#==========
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#=======
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# data dir
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#=======
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#indir = 'git/Data/pyrazinamide/input/original'
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indir = homedir + '/' + 'git/Data'
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datadir = homedir + '/' + 'git/Data'
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#===========
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# output dir
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#===========
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#=======
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# input
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#=======
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#indir = 'git/Data/pyrazinamide/input/original'
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in_filename = 'original_tanushree_data_v2.csv'
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infile = datadir + '/' + in_filename
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print('Input filename: ', in_filename
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, '\nInput path: ', indir)
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#=======
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# output
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#=======
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# several output files
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# output filenames in respective sections at the time of outputting files
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#outdir = 'git/Data/pyrazinamide/output'
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outdir = homedir + '/' + 'git/Data' + '/' + drug + '/' + 'output'
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outdir = datadir + '/' + drug + '/' + 'output'
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print('Output filename: in the respective sections'
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, '\nOutput path: ', outdir)
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#%%end of variable assignment for input and output files
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#==============================================================================
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#%% Read files
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in_filename = 'original_tanushree_data_v2.csv'
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infile = indir + '/' + in_filename
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print('Reading input master file:', infile)
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#=======================================================================
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#%% Read input file
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master_data = pd.read_csv(infile, sep = ',')
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# column names
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@ -1,13 +1,19 @@
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#!/usr/bin/python
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#%%
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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'''
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Created on Tue Aug 6 12:56:03 2019
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@author: tanu
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'''
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#=======================================================================
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# Task: Hydrophobicity (Kd) values for amino acid sequence using the Kyt&-Doolittle
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# Same output as using the expasy server https://web.expasy.org/protscale/
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# useful links
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# https://biopython.org/DIST/docs/api/Bio.SeqUtils.ProtParamData-pysrc.html
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# https://jbloomlab.github.io/dms_tools2/dms_tools2.dssp.html
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#%%
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# load packages
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#=======================================================================
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#%% load packages
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from pylab import *
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from Bio.SeqUtils import ProtParamData
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from Bio.SeqUtils.ProtParam import ProteinAnalysis
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@ -17,25 +23,46 @@ from Bio import SeqIO
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import pandas as pd
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import numpy as np
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import sys, os
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#%%
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# specify input and output variables
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#%% specify input and output variables
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homedir = os.path.expanduser('~')
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# set working dir
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os.getcwd()
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os.chdir(homedir + '/git/LSHTM_analysis/meta_data_analysis')
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os.getcwd()
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#=======================================================================
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#%% variable assignment: input and output paths & filenames
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drug = 'pyrazinamide'
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gene = 'pncA'
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gene_match = gene + '_p.'
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#==========
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# data dir
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#==========
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#indir = 'git/Data/pyrazinamide/input/original'
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datadir = homedir + '/' + 'git/Data'
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#=======
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# input
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#=======
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indir = 'git/Data/pyrazinamide/input/original'
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in_filename = "3pl1.fasta.txt"
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infile = homedir + '/' + indir + '/' + in_filename
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print(infile)
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#indir = 'git/Data/pyrazinamide/input/original'
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indir = datadir + '/' + drug + '/' + 'input'
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in_filename = '3pl1.fasta.txt'
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infile = indir + '/' + in_filename
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print('Input filename:', in_filename
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, '\nInput path:', indir)
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#=======
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# output
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#=======
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outdir = 'git/Data/pyrazinamide/output'
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out_filename = "kd.csv"
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outfile = homedir + '/' + outdir + '/' + out_filename
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print(outfile)
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#%%
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outdir = datadir + '/' + drug + '/' + 'output'
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out_filename = gene.lower() + '_kd.csv'
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outfile = outdir + '/' + out_filename
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print('Output filename:', out_filename
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, '\nOutput path:', outdir)
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#%%11
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# specify window size for hydropathy profile computation
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# https://web.expasy.org/protscale/pscale/protscale_help.html
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my_window = 3
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@ -43,7 +70,7 @@ offset = round((my_window/2)-0.5)
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fh = open(infile)
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for record in SeqIO.parse(fh, "fasta"):
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for record in SeqIO.parse(fh, 'fasta'):
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id = record.id
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seq = record.seq
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num_residues = len(seq)
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@ -60,11 +87,23 @@ print('Sequence Length:', num_residues)
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print('kd_values Length:',len(kd_values))
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print('Window Length:', my_window)
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print('Window Offset:', offset)
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print('======================================================================')
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print('Checking:len(kd values) is as expected for the given window size & offset...')
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expected_length = num_residues - (my_window - offset)
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if len(kd_values) == expected_length:
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print('PASS: expected and actual length of kd values match')
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else:
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print('FAIL: length mismatch'
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,'\nExpected length:', expected_length
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,'\nActual length:', len(kd_values))
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# make a df each for; aa sequence and kd_values. Then reset index for each df which will allow easy merging of the two
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print('======================================================================')
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#%% make 2 dfs; 1) aa sequence and 2) kd_values. Then reset index for each df
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# which will allow easy merging of the two dfs.
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# df1: df of aa seq with index reset to start from 1 (reflective of the actual aa position in a sequence)
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dfSeq = pd.DataFrame({'aa_wt':list(sequence)})
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# col name for wt is the same as reflected in the the AF_OR file to allow easy merging
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dfSeq = pd.DataFrame({'wild_type':list(sequence)})
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dfSeq.index = np.arange(1, len(dfSeq) + 1) # python is not inclusive
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# df2: df of kd_values with index reset to start from offset + 1 and subsequent matched length of the kd_values
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@ -76,19 +115,35 @@ max(dfVals['kd_values'])
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min(dfVals['kd_values'])
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# Merge the two on index (as these are now reflective of the aa position numbers): df1 and df2
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# This will introduce NaN where there is missing values. In our case this will be 2 (first and last ones)
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# Conveniently, the last position in this case is not part of the struc, so not much loss of info
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# Needless to state that this will be variable for other targets.
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df = pd.concat([dfSeq, dfVals], axis = 1)
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# rename index to position
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df = df.rename_axis('position')
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print(df)
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#%%
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# write file
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#%% write file
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print('Writing file:', out_filename
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, '\nFilename:', out_filename
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, '\nPath:', outdir)
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df.to_csv(outfile, header = True, index = True)
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print('Finished writing:', out_filename
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, '\nNo. of rows:', len(df)
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, '\nNo. of cols:', len(df.columns))
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#%% Plot
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# http://www.dalkescientific.com/writings/NBN/plotting.html
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# FIXME: save fig
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# extract just pdb if from 'id' to pass to title of plot
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# foo = re.match(r'(^[0-9]{1}\w{3})', id).groups(1)
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plot(kd_values, linewidth = 1.0)
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#axis(xmin = 1, xmax = num_residues)
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xlabel("Residue Number")
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ylabel("Hydrophobicity")
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title("K&D Hydrophobicity for " + id)
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xlabel('Residue Number')
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ylabel('Hydrophobicity')
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title('K&D Hydrophobicity for ' + id)
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show()
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#%% end of script
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@ -7,29 +7,25 @@ Created on Tue Aug 6 12:56:03 2019
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'''
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# FIXME: import dirs.py to get the basic dir paths available
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#%% load libraries
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###################
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# load libraries
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import os, sys
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import pandas as pd
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#import numpy as np
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#====================================================
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#=======================================================================
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# TASK: calculate how many mutations result in
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# electrostatic changes wrt wt
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# Input: mcsm and AF_OR file
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# Output: mut_elec_changes_results.txt
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#========================================================
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#=======================================================================
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#%% load libraries
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import os, sys
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import pandas as pd
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#import numpy as np
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#%% specify homedir as python doesn't recognise tilde
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homedir = os.path.expanduser('~')
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# my working dir
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# set working dir
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os.getcwd()
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os.chdir(homedir + '/git/LSHTM_analysis/meta_data_analysis')
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os.getcwd()
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#========================================================
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#=======================================================================
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#%% variable assignment: input and output paths & filenames
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drug = 'pyrazinamide'
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gene = 'pncA'
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@ -41,28 +37,29 @@ gene_match = gene + '_p.'
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#indir = 'git/Data/pyrazinamide/input/original'
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datadir = homedir + '/' + 'git/Data'
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#==========
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# input dir
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#==========
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#=======
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# input
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#=======
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indir = datadir + '/' + drug + '/' + 'input'
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in_filename = 'merged_df3.csv'
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infile = outdir + '/' + in_filename
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print('Input filename: ', in_filename
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, '\nInput path: ', indir)
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#============
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# output dir
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#============
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# several output files
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#=======
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# output
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#=======
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outdir = datadir + '/' + drug + '/' + 'output'
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# specify output file
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out_filename = 'mut_elec_changes.txt'
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outfile = outdir + '/' + out_filename
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print('Output path: ', outdir)
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print('Output filename: ', out_filename
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, '\nOutput path: ', outdir)
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#%% end of variable assignment for input and output files
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#=============================================================
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#=======================================================================
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#%% Read input files
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#in_filename = gene.lower() + '_meta_data_with_AFandOR.csv'
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in_filename = 'merged_df3.csv'
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infile = outdir + '/' + in_filename
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print('Reading input file (merged file):', infile)
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comb_df = pd.read_csv(infile, sep = ',')
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