Bio Format Conversion

from Bio import SeqIO

Core Function

SeqIO.convert() - Direct Conversion

Convert between formats in a single call. Most efficient method.

count = SeqIO.convert('input.gb', 'genbank', 'output.fasta', 'fasta')
print(f'Converted {count} records')

Parameters:

• in_file - Input filename or handle
• in_format - Input format string
• out_file - Output filename or handle
• out_format - Output format string

Returns: Number of records converted

Common Conversions

Code Patterns

Simple Conversion

SeqIO.convert('input.gb', 'genbank', 'output.fasta', 'fasta')

GenBank to FASTA

SeqIO.convert('sequence.gb', 'genbank', 'sequence.fasta', 'fasta')

FASTQ to FASTA (drop quality)

SeqIO.convert('reads.fastq', 'fastq', 'reads.fasta', 'fasta')

FASTA to GenBank (requires molecule_type)

Goal: Convert FASTA to GenBank format, which requires molecule_type annotation.

Approach: Stream records through a generator that injects the missing annotation, then write.

Reference (BioPython 1.83+):

records = SeqIO.parse('input.fasta', 'fasta')
def add_molecule_type(records):
    for record in records:
        record.annotations['molecule_type'] = 'DNA'
        yield record

SeqIO.write(add_molecule_type(records), 'output.gb', 'genbank')

FASTA to FASTQ (add dummy quality)

Goal: Convert FASTA to FASTQ by assigning uniform placeholder quality scores.

Approach: Stream records through a generator that adds phred_quality to each, then write as FASTQ.

Reference (BioPython 1.83+):

def add_quality(records, quality=30):
    for record in records:
        record.letter_annotations['phred_quality'] = [quality] * len(record.seq)
        yield record

records = SeqIO.parse('input.fasta', 'fasta')
SeqIO.write(add_quality(records), 'output.fastq', 'fastq')

Batch Convert Multiple Files

Goal: Convert all files of one format in a directory to another format.

Approach: Glob for input files, apply SeqIO.convert() to each, and report per-file counts.

Reference (BioPython 1.83+):

from pathlib import Path

for gb_file in Path('.').glob('*.gb'):
    fasta_file = gb_file.with_suffix('.fasta')
    count = SeqIO.convert(str(gb_file), 'genbank', str(fasta_file), 'fasta')
    print(f'{gb_file.name}: {count} records')

Convert with Modifications

from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord

def uppercase_record(rec):
    return SeqRecord(rec.seq.upper(), id=rec.id, description=rec.description)

records = SeqIO.parse('input.fasta', 'fasta')
modified = (uppercase_record(rec) for rec in records)
SeqIO.write(modified, 'output.fasta', 'fasta')

Alignment Format Conversion

from Bio import AlignIO

AlignIO.convert('alignment.sto', 'stockholm', 'alignment.phy', 'phylip')

Format Compatibility Matrix

Can convert directly (no modifications needed):

• GenBank <-> EMBL
• FASTA -> any format (may need annotations added)
• Any format -> FASTA (always works, may lose data)
• FASTQ -> FASTA

Requires adding data:

• FASTA -> FASTQ (need quality scores)
• FASTA -> GenBank (need molecule_type)

May lose data:

• GenBank -> FASTA (loses features, annotations)
• FASTQ -> FASTA (loses quality scores)
• Any rich format -> FASTA

Common Errors

Decision Tree

Converting formats?
├── Simple conversion (no data changes)?
│   └── Use SeqIO.convert() directly
├── Need to add annotations?
│   └── Parse, modify records, then write
├── Need to transform sequences?
│   └── Parse, apply transformation, then write
└── Multiple files?
    └── Loop with SeqIO.convert() or batch generator

Related Skills

• read-sequences - Parse sequences for custom conversion logic
• write-sequences - Write converted sequences with modifications
• batch-processing - Convert multiple files at once
• compressed-files - Handle compressed input/output during conversion
• alignment-files - For SAM/BAM/CRAM conversion, use samtools view