matrix_file = <str:1> | 'family.mat' | the filename of the pairwise distance matrix |
output_directory = <str:1> | '' | output directory |
In addition to the output in the log file, this routine creates file output_directory/matrix_file with pairwise sequence distances that can be used directly as the input to the tree making programs of the PHYLIP package, such as KITSCH [Felsenstein, 1985], and also for the environ.dendrogram() and environ.principal_components() commands. A more general version of this command, which allows a user specified measure for residue-residue differences is alignment.compare_sequences().
# Example for: alignment.id_table(), alignment.compare_sequences(), # misc.principal_components(), misc.dendrogram() # Pairwise sequence identity between sequences in the alignment. env = environ() # Read all entries in this alignment: aln = alignment(env, file='toxin.ali') # Calculate pairwise sequence identities: aln.id_table(matrix_file='toxin_id.mat') # Calculate pairwise sequence similarities: mdl = model(env, file='2ctx', model_segment=('1:', '71:')) aln.compare_sequences(mdl, rr_file='$(LIB)/as1.sim.mat', max_gaps_match=1, matrix_file='toxin.mat', variability_file='toxin.var') mdl.write(file='2ctx.var') # Do principal components clustering using sequence similarities: env.principal_components(matrix_file='toxin.mat', file='toxin.princ') # Dendrogram in the log file: env.dendrogram(matrix_file='toxin.mat')