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bio-alignment-io

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.

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FreedomIntelligence/OpenClaw-Medical-Skills

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包含的文件（7）

SKILL.md9.5 KB
examples/batch_convert.py645 B
examples/convert_formats.py615 B
examples/read_alignment.py499 B
examples/sample_alignment.aln237 B
examples/slice_alignment.py686 B
usage-guide.md2.2 KB

SKILL.md（原文）

安装前可以查看交给 AI 代理的指令内容。

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-Specific Notes

PHYLIP Format

# Standard PHYLIP (10 char names, interleaved)
alignment = AlignIO.read('file.phy', 'phylip')

# Sequential PHYLIP
alignment = AlignIO.read('file.phy', 'phylip-sequential')

# Relaxed PHYLIP (allows longer names)
alignment = AlignIO.read('file.phy', 'phylip-relaxed')

Stockholm Format (with Annotations)

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

# Access annotations
for record in alignment:
    print(record.id, record.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

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

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