# Sequence Coverage Plotting¶

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 """ Contact Map Precision Evaluation ================================ This script contains a simple example of how you can evaluate the precision scores of your contact map using ConKit """ import conkit.io import conkit.plot # Define the input variables sequence_file = "toxd/toxd.fasta" sequence_format = "fasta" contact_file = "toxd/toxd.mat" contact_format = "ccmpred" # Create ConKit hierarchies # Note, we only need the first Sequence/ContactMap # from each file seq = conkit.io.read(sequence_file, sequence_format).top conpred = conkit.io.read(contact_file, contact_format).top # Assign the sequence register to your contact prediction conpred.sequence = seq conpred.set_sequence_register() # We need to tidy our contact prediction before plotting conpred.remove_neighbors(inplace=True) conpred.sort('raw_score', reverse=True, inplace=True) # ==================================================== # The code above is identical to the previous example # Now we need to compare it to our reference structure pdb_file = "toxd/toxd.pdb" pdb = conkit.io.read(pdb_file, "pdb").top # The two keywords do the following: # - remove_unmatched : remove contacts absent from the pdb_file # - renumber : match the numbering to the pdb_file map_matched = map.match(pdb, remove_unmatched=True, renumber=True) # Then we can plot the evaluation plot fig = conkit.plot.PrecisionEvaluationFigure(map_matched, cutoff_step=0.1, min_cutoff=0.0, max_cutoff=2.0, legend=True) fig.savefig("toxd/cdens.png")