alignment-io

name	alignment-io
description	Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and other alignment formats for phylogenetics and conservation analysis. Use when reading, writing, or converting alignment file formats.
tool_type	python
primary_tool	Bio.AlignIO

Version Compatibility

Reference examples tested with: BioPython 1.83+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Alignment File I/O

Read, write, and convert multiple sequence alignment files in various formats.

Required Import

Goal: Load modules for reading, writing, and manipulating multiple sequence alignments.

Approach: Import AlignIO for file I/O and supporting classes for programmatic alignment construction.

from Bio import AlignIO
from Bio.Align import MultipleSeqAlignment
from Bio.SeqRecord import SeqRecord
from Bio.Seq import Seq

Supported Formats

Format	Extension	Read	Write	Description
clustal	.aln	Yes	Yes	Clustal W/X output
fasta	.fasta, .fa	Yes	Yes	Aligned FASTA
phylip	.phy	Yes	Yes	Interleaved PHYLIP
phylip-sequential	.phy	Yes	Yes	Sequential PHYLIP
phylip-relaxed	.phy	Yes	Yes	PHYLIP with long names
stockholm	.sto, .stk	Yes	Yes	Pfam/Rfam annotated
nexus	.nex	Yes	Yes	NEXUS format
emboss	.txt	Yes	No	EMBOSS tools output
fasta-m10	.txt	Yes	No	FASTA -m 10 output
maf	.maf	Yes	Yes	Multiple Alignment Format
mauve	.xmfa	Yes	No	progressiveMauve output
msf	.msf	Yes	No	GCG MSF format

Reading Alignments

"Read an alignment file" → Parse an alignment file into an alignment object with sequences and metadata accessible.

Goal: Load alignment data from files in various formats (Clustal, PHYLIP, Stockholm, FASTA).

Approach: Use AlignIO.read() for single-alignment files or AlignIO.parse() for files containing multiple alignments.

Single Alignment File

from Bio import AlignIO

alignment = AlignIO.read('alignment.aln', 'clustal')
print(f'Alignment length: {alignment.get_alignment_length()}')
print(f'Number of sequences: {len(alignment)}')

Multiple Alignments in One File

for alignment in AlignIO.parse('multi_alignment.sto', 'stockholm'):
    print(f'Alignment with {len(alignment)} sequences, length {alignment.get_alignment_length()}')

Read as List

alignments = list(AlignIO.parse('alignments.phy', 'phylip'))
print(f'Read {len(alignments)} alignments')

Writing Alignments

Goal: Save alignment data to files in standard formats for downstream tools or archival.

Approach: Use AlignIO.write() with the target format specifier, supporting single or multiple alignments and file handles.

Write Single Alignment

AlignIO.write(alignment, 'output.fasta', 'fasta')

Write Multiple Alignments

alignments = [alignment1, alignment2, alignment3]
count = AlignIO.write(alignments, 'output.sto', 'stockholm')
print(f'Wrote {count} alignments')

Write to Handle

with open('output.aln', 'w') as handle:
    AlignIO.write(alignment, handle, 'clustal')

Format Conversion

"Convert alignment format" → Transform an alignment file from one format to another (e.g., Clustal to PHYLIP).

Goal: Convert alignment files between formats for compatibility with different analysis tools.

Approach: Use AlignIO.convert() for direct one-step conversion, or read-modify-write for cases requiring intermediate manipulation.

Direct Conversion (Most Efficient)

AlignIO.convert('input.aln', 'clustal', 'output.phy', 'phylip')

With Alphabet Specification

AlignIO.convert('input.sto', 'stockholm', 'output.nex', 'nexus', molecule_type='DNA')

Manual Conversion (When Modification Needed)

alignment = AlignIO.read('input.aln', 'clustal')
# ... modify alignment ...
AlignIO.write(alignment, 'output.fasta', 'fasta')

Accessing Alignment Data

Goal: Navigate and extract data from alignment objects including sequences, columns, and slices.

Approach: Use iteration, indexing, and column slicing on the alignment object.

alignment = AlignIO.read('alignment.aln', 'clustal')

# Iterate over sequences
for record in alignment:
    print(f'{record.id}: {record.seq}')

# Access by index
first_seq = alignment[0]
last_seq = alignment[-1]

# Slice columns
column_slice = alignment[:, 10:20]  # Columns 10-19

# Get specific column
column = alignment[:, 5]  # Column 5 as string

Working with Alignment Objects

Get Alignment Properties

alignment = AlignIO.read('alignment.aln', 'clustal')

length = alignment.get_alignment_length()
num_seqs = len(alignment)
seq_ids = [record.id for record in alignment]

Slice Alignments

# Get subset of sequences
subset = alignment[0:5]  # First 5 sequences

# Get subset of columns
trimmed = alignment[:, 50:150]  # Columns 50-149

# Combine slicing
region = alignment[0:5, 50:150]  # 5 sequences, columns 50-149

Creating Alignments Programmatically

Goal: Build an alignment object from sequences defined in code rather than read from a file.

Approach: Construct SeqRecord objects with gap characters and wrap them in a MultipleSeqAlignment.

from Bio.Align import MultipleSeqAlignment
from Bio.SeqRecord import SeqRecord
from Bio.Seq import Seq

records = [
    SeqRecord(Seq('ACTGACTGACTG'), id='seq1'),
    SeqRecord(Seq('ACTGACT-ACTG'), id='seq2'),
    SeqRecord(Seq('ACTG-CTGACTG'), id='seq3'),
]
alignment = MultipleSeqAlignment(records)
AlignIO.write(alignment, 'new_alignment.fasta', 'fasta')

Format Selection for Downstream Tools

Choosing the output format depends on which downstream tool consumes the alignment:

Downstream Tool	Required Format	BioPython Format String
RAxML-NG, IQ-TREE	PHYLIP (relaxed)	'phylip-relaxed'
MrBayes	NEXUS	'nexus'
PAUP*	NEXUS or PHYLIP	'nexus' or 'phylip'
HMMER, Infernal	Stockholm	'stockholm'
Pfam/Rfam databases	Stockholm	'stockholm'
PAML/codeml	PHYLIP (sequential)	'phylip-sequential'
Most tools	FASTA	'fasta'

Annotation Preservation

Not all formats support annotations. Converting between formats can silently discard metadata:

Format	Sequence Annotations	Column Annotations	Secondary Structure
Stockholm	Yes (GS/GR lines)	Yes (GC lines)	Yes (SS_cons)
NEXUS	Partial (SETS block)	Via CHARSET	No
Clustal	No (conservation marks not parsed)	No	No
PHYLIP	No	No	No
FASTA	No	No	No

Converting Stockholm to FASTA or PHYLIP discards all annotations, secondary structure markup, and per-residue quality scores. If annotations matter, keep a Stockholm master copy.

Format-Specific Notes

PHYLIP Format Pitfalls

PHYLIP has two incompatible variants (interleaved vs sequential) and two name-length modes (strict vs relaxed). Confusing these causes silent data corruption.

Strict PHYLIP truncates sequence names to exactly 10 characters. This can silently merge distinct sequences whose names share a 10-character prefix (e.g., Homo_sapiens_chr1 and Homo_sapiens_chr2 both become Homo_sapie).

# Strict PHYLIP (10-char names, interleaved) -- only for tools requiring it
alignment = AlignIO.read('file.phy', 'phylip')

# Sequential PHYLIP (10-char names, one sequence at a time) -- PAML/codeml
alignment = AlignIO.read('file.phy', 'phylip-sequential')

# Relaxed PHYLIP (no name limit) -- RAxML-NG, IQ-TREE (recommended default)
alignment = AlignIO.read('file.phy', 'phylip-relaxed')

# Always prefer phylip-relaxed for writing unless the downstream tool
# specifically requires strict format
AlignIO.write(alignment, 'output.phy', 'phylip-relaxed')

Stockholm Format Annotations

Stockholm format (used by Pfam, Rfam, HMMER) supports four annotation line types:

Line Prefix	Scope	Description	Example
#=GF	File	Alignment-level metadata (ID, accession, description)	#=GF AC PF00001
#=GC	Column	Per-column annotation (1 char per alignment column)	#=GC SS_cons ..(((...)))..
#=GS	Sequence	Per-sequence free text (organism, description)	#=GS seq1 OS Homo sapiens
#=GR	Residue	Per-residue annotation (1 char per residue)	#=GR seq1 SS ..HHH..EEE..

Common GC annotations: SS_cons (consensus secondary structure), RF (reference coordinates), seq_cons (consensus sequence). RNA families in Rfam use <> for base pairs, . for unpaired.

alignment = AlignIO.read('pfam.sto', 'stockholm')

for record in alignment:
    print(record.id, record.annotations)
    if 'secondary_structure' in record.letter_annotations:
        print(f'  SS: {record.letter_annotations["secondary_structure"]}')

# Column annotations are accessible via alignment.column_annotations

Clustal Format

# Clustal preserves conservation symbols in file but not when parsed
alignment = AlignIO.read('clustal.aln', 'clustal')

Batch Processing Multiple Files

Goal: Convert a directory of alignment files from one format to another in bulk.

Approach: Glob for input files and iterate, reading each alignment and writing to the target format.

from pathlib import Path

input_dir = Path('alignments/')
output_dir = Path('converted/')

for input_file in input_dir.glob('*.aln'):
    alignment = AlignIO.read(input_file, 'clustal')
    output_file = output_dir / f'{input_file.stem}.fasta'
    AlignIO.write(alignment, output_file, 'fasta')

Alternative: Bio.Align Module I/O

Goal: Use the modern Bio.Align module for alignment I/O with access to newer features like counts and substitutions.

Approach: Use Align.read(), Align.parse(), and Align.write() which return Alignment objects instead of MultipleSeqAlignment.

The newer Bio.Align module provides its own I/O functions that return Alignment objects (instead of MultipleSeqAlignment). These support additional formats and provide access to modern alignment features.

from Bio import Align

# Read single alignment (returns Alignment object)
alignment = Align.read('alignment.aln', 'clustal')

# Parse multiple alignments
for alignment in Align.parse('multi.sto', 'stockholm'):
    print(f'Alignment with {len(alignment)} sequences')

# Write alignment
Align.write(alignment, 'output.fasta', 'fasta')

When to Use Which

Use Case	Module
Legacy code, MultipleSeqAlignment needed	Bio.AlignIO
Modern features (counts, substitutions)	Bio.Align
Format conversion	Either works
Working with pairwise alignments	Bio.Align

Quick Reference: Common Operations

Task	Code
Read single alignment	AlignIO.read(file, format)
Read multiple alignments	AlignIO.parse(file, format)
Write alignment(s)	AlignIO.write(align, file, format)
Convert format	AlignIO.convert(in_file, in_fmt, out_file, out_fmt)
Get length	alignment.get_alignment_length()
Get sequence count	len(alignment)
Slice columns	alignment[:, start:end]

Common Errors

Error	Cause	Solution
ValueError: No records	Empty file	Check file path and format
ValueError: More than one record	Multiple alignments with read()	Use parse() instead
ValueError: Sequences different lengths	Invalid alignment	Ensure all sequences same length
ValueError: unknown format	Unsupported format string	Check supported formats list

Related Skills

• multiple-alignment - Run MSA tools (MAFFT, MUSCLE5, ClustalOmega) to generate alignments
• pairwise-alignment - Create pairwise alignments with PairwiseAligner
• msa-parsing - Analyze alignment content and annotations
• msa-statistics - Calculate conservation and identity
• sequence-io/format-conversion - Convert sequence (non-alignment) formats