85 lines
No EOL
2.5 KiB
Python
Executable file
85 lines
No EOL
2.5 KiB
Python
Executable file
#!/home/tanu/anaconda3/envs/ContactMap/bin/python3
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# Read a DSSP file into a data frame and pretty-print it
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#https://jbloomlab.github.io/dms_tools2/dms_tools2.dssp.html
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#https://jbloomlab.github.io/dms_tools2/dms_tools2.dssp.html
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import sys, os
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import re
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import pandas as pd
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from Bio.PDB import PDBParser
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from Bio.PDB.DSSP import DSSP
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import pandas as pd
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import pprint as pp
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#from Bio.PDB.PDBParser import PDBParser
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import dms_tools2
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import dms_tools2.dssp
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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 = datadir + '/' + drug + '/' + 'output'
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#in_filename = 'pnca.dssp'
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in_filename = gene.lower() +'.dssp'
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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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# specify PDB chain
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my_chain = 'A'
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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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out_filename = gene.lower() + '_dssp_df'
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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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,'\nOutfile: ', outfile)
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#%% end of variable assignment for input and output files
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#================================================================
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# Process dssp output and extract into df
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dssp_file = infile
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dssp_df = dms_tools2.dssp.processDSSP(dssp_file, chain = my_chain)
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# returns df with ASA and RSA (base on Tien at al 2013 (theor.) values)
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# Link: https://en.wikipedia.org/wiki/Relative_accessible_surface_area
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pp.pprint(dssp_df)
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# Rename column (amino acid) as 'wild_type' and (site} as 'position'
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# to be the same names as used in the file required for merging later.
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dssp_df.columns
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dssp_df.rename(columns = {'site':'position', 'amino_acid':'wild_type'}, inplace = True)
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dssp_df.columns
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#%% Write ouput csv file
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print('Writing file:', outfile
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, '\nFilename:', out_filename
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, '\nPath:', outdir)
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# write to csv
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dssp_df.to_csv(outfile, header=True, index = False)
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print('Finished writing:', out_filename
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, '\nNo. of rows:', len(dssp_df)
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, '\nNo. of cols:', len(dssp_df.columns))
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print('======================================================================') |