# Copyright 2016 by Peter Cock. All rights reserved. # This code is part of the Biopython distribution and governed by its # license. Please see the LICENSE file that should have been included # as part of this package. """Bio.Align.AlignInfo related tests.""" import unittest from Bio.Align import MultipleSeqAlignment from Bio.Seq import Seq from Bio.SeqRecord import SeqRecord from Bio import AlignIO from Bio.Align.AlignInfo import SummaryInfo from Bio.Data import IUPACData import math class AlignInfoTests(unittest.TestCase): """Test basic usage.""" def assertAlmostEqualList(self, list1, list2, **kwargs): self.assertEqual(len(list1), len(list2)) for (v1, v2) in zip(list1, list2): self.assertAlmostEqual(v1, v2, **kwargs) def test_nucleotides(self): filename = "GFF/multi.fna" fmt = "fasta" alignment = AlignIO.read(filename, fmt) summary = SummaryInfo(alignment) c = summary.dumb_consensus(ambiguous="N") self.assertEqual(str(c), "NNNNNNNN") c = summary.gap_consensus(ambiguous="N") self.assertEqual(str(c), "NNNNNNNN") expected = {"A": 0.25, "G": 0.25, "T": 0.25, "C": 0.25} m = summary.pos_specific_score_matrix(chars_to_ignore=["-"], axis_seq=c) self.assertEqual( str(m), """ A C G T N 2.0 0.0 1.0 0.0 N 1.0 1.0 1.0 0.0 N 1.0 0.0 2.0 0.0 N 0.0 1.0 1.0 1.0 N 1.0 2.0 0.0 0.0 N 0.0 2.0 1.0 0.0 N 1.0 2.0 0.0 0.0 N 0.0 2.0 1.0 0.0 """, ) # provide the frequencies and chars to ignore explicitly. ic = summary.information_content(e_freq_table=expected, chars_to_ignore=["-"]) self.assertAlmostEqual(ic, 7.32029999423075, places=6) def test_proteins(self): a = MultipleSeqAlignment( [ SeqRecord(Seq("MHQAIFIYQIGYP*LKSGYIQSIRSPEYDNW-"), id="ID001"), SeqRecord(Seq("MH--IFIYQIGYAYLKSGYIQSIRSPEY-NW*"), id="ID002"), SeqRecord(Seq("MHQAIFIYQIGYPYLKSGYIQSIRSPEYDNW*"), id="ID003"), ] ) self.assertEqual(32, a.get_alignment_length()) s = SummaryInfo(a) c = s.dumb_consensus(ambiguous="X") self.assertEqual(str(c), "MHQAIFIYQIGYXXLKSGYIQSIRSPEYDNW*") c = s.gap_consensus(ambiguous="X") self.assertEqual(str(c), "MHXXIFIYQIGYXXLKSGYIQSIRSPEYXNWX") m = s.pos_specific_score_matrix(chars_to_ignore=["-", "*"], axis_seq=c) self.assertEqual( str(m), """ A D E F G H I K L M N P Q R S W Y M 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 H 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 X 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 0.0 X 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 I 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 F 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 I 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Y 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 Q 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 I 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 G 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Y 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 X 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 0.0 0.0 X 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.0 L 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 K 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 S 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 G 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Y 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 I 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Q 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 S 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 I 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 R 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 S 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 P 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 E 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Y 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 X 0.0 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 N 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 W 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 X 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 """, ) letters = IUPACData.protein_letters base_freq = 1.0 / len(letters) e_freq_table = {letter: base_freq for letter in letters} ic = s.information_content( e_freq_table=e_freq_table, chars_to_ignore=["-", "*"] ) self.assertAlmostEqual(ic, 133.061475107, places=6) def test_pseudo_count(self): # use example from # http://biologie.univ-mrs.fr/upload/p202/01.4.PSSM_theory.pdf dna_align = MultipleSeqAlignment( [ SeqRecord(Seq("AACCACGTTTAA"), id="ID001"), SeqRecord(Seq("CACCACGTGGGT"), id="ID002"), SeqRecord(Seq("CACCACGTTCGC"), id="ID003"), SeqRecord(Seq("GCGCACGTGGGG"), id="ID004"), SeqRecord(Seq("TCGCACGTTGTG"), id="ID005"), SeqRecord(Seq("TGGCACGTGTTT"), id="ID006"), SeqRecord(Seq("TGACACGTGGGA"), id="ID007"), SeqRecord(Seq("TTACACGTGCGC"), id="ID008"), ] ) summary = SummaryInfo(dna_align) expected = {"A": 0.325, "G": 0.175, "T": 0.325, "C": 0.175} ic = summary.information_content( e_freq_table=expected, log_base=math.exp(1), pseudo_count=1 ) self.assertAlmostEqualList( summary.ic_vector, [ 0.110, 0.090, 0.360, 1.290, 0.800, 1.290, 1.290, 0.80, 0.610, 0.390, 0.470, 0.040, ], places=2, ) self.assertAlmostEqual(ic, 7.546, places=3) if __name__ == "__main__": runner = unittest.TextTestRunner(verbosity=2) unittest.main(testRunner=runner)