Bio.SeqIO.AceIO module

Bio.SeqIO support for the “ace” file format.

You are expected to use this module via the Bio.SeqIO functions. See also the Bio.Sequencing.Ace module which offers more than just accessing the contig consensus sequences in an ACE file as SeqRecord objects.

Bio.SeqIO.AceIO.AceIterator(source)

Return SeqRecord objects from an ACE file.

This uses the Bio.Sequencing.Ace module to do the hard work. Note that by iterating over the file in a single pass, we are forced to ignore any WA, CT, RT or WR footer tags.

Ace files include the base quality for each position, which are taken to be PHRED style scores. Just as if you had read in a FASTQ or QUAL file using PHRED scores using Bio.SeqIO, these are stored in the SeqRecord’s letter_annotations dictionary under the “phred_quality” key.

>>> from Bio import SeqIO
>>> with open("Ace/consed_sample.ace") as handle:
...     for record in SeqIO.parse(handle, "ace"):
...         print("%s %s... %i" % (record.id, record.seq[:10], len(record)))
...         print(max(record.letter_annotations["phred_quality"]))
Contig1 agccccgggc... 1475
90

However, ACE files do not include a base quality for any gaps in the consensus sequence, and these are represented in Biopython with a quality of zero. Using zero is perhaps misleading as there may be very strong evidence to support the gap in the consensus. Previous versions of Biopython therefore used None instead, but this complicated usage, and prevented output of the gapped sequence as FASTQ format.

>>> from Bio import SeqIO
>>> with open("Ace/contig1.ace") as handle:
...     for record in SeqIO.parse(handle, "ace"):
...         print("%s ...%s..." % (record.id, record.seq[85:95]))
...         print(record.letter_annotations["phred_quality"][85:95])
...         print(max(record.letter_annotations["phred_quality"]))
Contig1 ...AGAGG-ATGC...
[57, 57, 54, 57, 57, 0, 57, 72, 72, 72]
90
Contig2 ...GAATTACTAT...
[68, 68, 68, 68, 68, 68, 68, 68, 68, 68]
90