Bio.codonalign package

Submodules

• Bio.codonalign.codonalignment module
  • CodonAlignment
    • CodonAlignment.__init__()
    • CodonAlignment.__str__()
    • CodonAlignment.__getitem__()
    • CodonAlignment.__add__()
    • CodonAlignment.get_aln_length()
    • CodonAlignment.toMultipleSeqAlignment()
    • CodonAlignment.get_dn_ds_matrix()
    • CodonAlignment.get_dn_ds_tree()
    • CodonAlignment.from_msa()
    • CodonAlignment.__annotations__
  • mktest()
• Bio.codonalign.codonseq module
  • CodonSeq
    • CodonSeq.__init__()
    • CodonSeq.get_codon()
    • CodonSeq.get_codon_num()
    • CodonSeq.translate()
    • CodonSeq.toSeq()
    • CodonSeq.get_full_rf_table()
    • CodonSeq.full_translate()
    • CodonSeq.ungap()
    • CodonSeq.from_seq()
    • CodonSeq.__abstractmethods__
    • CodonSeq.__annotations__
  • cal_dn_ds()

Module contents

Code for dealing with Codon Alignments.

Bio.codonalign.build(pro_align, nucl_seqs, corr_dict=None, gap_char='-', unknown='X', codon_table=None, complete_protein=False, anchor_len=10, max_score=10)

Build a codon alignment from protein alignment and corresponding nucleotides.

Arguments:

• pro_align - a protein MultipleSeqAlignment object

• nucl_seqs - an object returned by SeqIO.parse or SeqIO.index or a collection of SeqRecord.

• corr_dict - a dict that maps protein id to nucleotide id

• complete_protein - whether the sequence begins with a start codon

Return a CodonAlignment object.

The example below answers this Biostars question: https://www.biostars.org/p/89741/

>>> from Bio.Seq import Seq
>>> from Bio.SeqRecord import SeqRecord
>>> from Bio.Align import MultipleSeqAlignment
>>> from Bio.codonalign import build
>>> seq1 = SeqRecord(Seq('ATGTCTCGT'), id='pro1')
>>> seq2 = SeqRecord(Seq('ATGCGT'), id='pro2')
>>> pro1 = SeqRecord(Seq('MSR'), id='pro1')
>>> pro2 = SeqRecord(Seq('M-R'), id='pro2')
>>> aln = MultipleSeqAlignment([pro1, pro2])
>>> codon_aln = build(aln, [seq1, seq2])
>>> print(codon_aln)
CodonAlignment with 2 rows and 9 columns (3 codons)
ATGTCTCGT pro1
ATG---CGT pro2

Using the newer codon aligner in Bio.Align, this analysis can be performed as follows:

>>> from Bio.Align import PairwiseAligner, CodonAligner
>>> seq1 = SeqRecord(Seq('ATGTCTCGT'), id='pro1')
>>> seq2 = SeqRecord(Seq('ATGCGT'), id='pro2')
>>> pro1 = SeqRecord(Seq('MSR'), id='pro1')
>>> pro2 = SeqRecord(Seq('MR'), id='pro2')
>>> aligner = PairwiseAligner()
>>> protein_alignment = aligner.align(pro1, pro2)[0]
>>> print(protein_alignment)
pro1              0 MSR 3
                  0 |-| 3
pro2              0 M-R 2

>>> codon_aligner = CodonAligner()
>>> alignment1 = codon_aligner.align(pro1, seq1)[0]
>>> alignment2 = codon_aligner.align(pro2, seq2)[0]
>>> print(alignment1)
pro1              0 M  S  R   3
pro1              0 ATGTCTCGT 9

>>> print(alignment2)
pro2              0 M  R   2
pro2              0 ATGCGT 6

>>> codon_alignment = protein_alignment.mapall([alignment1, alignment2])
>>> print(codon_alignment)
pro1              0 ATGTCTCGT 9
                  0 |||---||| 9
pro2              0 ATG---CGT 6

>>> naive_alignment = aligner.align(seq1, seq2)[0]
>>> print(naive_alignment)
pro1              0 ATGTCTCGT 9
                  0 |||-|--|| 9
pro2              0 ATG-C--GT 6