/bio-format-conversion
Convert between sequence file formats (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO. Use when changing file formats or preparing data for different tools.
Claude Code
$ npx -y skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-format-conversion --agent claude-code
Codex
$ npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-format-conversion -a codex -y
Cursor
$ npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-format-conversion -a cursor -y
Gemini CLI
$ npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-format-conversion -a gemini-cli -y
GitHub Copilot
$ npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-format-conversion -a github-copilot -y
OpenCode
$ npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-format-conversion -a opencode -y
Windsurf
$ npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-format-conversion -a windsurf -y
SKILL.md
bio-format-conversion.SKILL.mdname: bio-format-conversion
description: Convert between sequence file formats (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO. Use when changing file formats or preparing data for different tools.
tool_type: python
primary_tool: Bio.SeqIO
Version Compatibility
Reference examples tested with: BioPython 1.83+, samtools 1.19+
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.
Format Conversion
**"Convert this file to a different format"** → Read records in one format, optionally add missing annotations, and write in the target format.
- Python: `SeqIO.convert()` for direct conversion, or `SeqIO.parse()` + `SeqIO.write()` when modifications are needed (BioPython)
- CLI: `seqkit seq` (SeqKit) for FASTA/FASTQ; `samtools view` for SAM/BAM/CRAM
Convert sequence files between formats using Biopython's Bio.SeqIO module.
Required Import
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
| From | To | Notes | |------|-----|-------| | GenBank | FASTA | Loses annotations, keeps sequence | | FASTA | GenBank | Need to add molecule_type | | FASTQ | FASTA | Loses quality scores | | FASTA | FASTQ | Need to add quality scores | | GenBank | EMBL | Usually works directly | | Stockholm | FASTA | Alignment to sequences |
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
| Error | Cause | Solution | |-------|-------|----------| | `ValueError: missing molecule_type` | FASTA to GenBank | Add molecule_type annotation | | `ValueError: missing quality scores` | FASTA to FASTQ | Add phred_quality to letter_annotations | | `KeyError: 'phred_quality'` | Wrong FASTQ variant | Try 'fastq-sanger', 'fastq-illumina' |
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 generatorRelated 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
Read more
name: bio-format-conversion description: Convert between sequence file formats (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO. Use when changing file formats or preparing data for different tools. tool_type: python primary_tool: Bio.SeqIO
Version Compatibility
Reference examples tested with: BioPython 1.83+, samtools 1.19+
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.
Format Conversion
**"Convert this file to a different format"** → Read records in one format, optionally add missing annotations, and write in the target format.
- Python: `SeqIO.convert()` for direct conversion, or `SeqIO.parse()` + `SeqIO.write()` when modifications are needed (BioPython)
- CLI: `seqkit seq` (SeqKit) for FASTA/FASTQ; `samtools view` for SAM/BAM/CRAM
Convert sequence files between formats using Biopython's Bio.SeqIO module.
Required Import
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
| From | To | Notes | |------|-----|-------| | GenBank | FASTA | Loses annotations, keeps sequence | | FASTA | GenBank | Need to add molecule_type | | FASTQ | FASTA | Loses quality scores | | FASTA | FASTQ | Need to add quality scores | | GenBank | EMBL | Usually works directly | | Stockholm | FASTA | Alignment to sequences |
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
| Error | Cause | Solution | |-------|-------|----------| | `ValueError: missing molecule_type` | FASTA to GenBank | Add molecule_type annotation | | `ValueError: missing quality scores` | FASTA to FASTQ | Add phred_quality to letter_annotations | | `KeyError: 'phred_quality'` | Wrong FASTQ variant | Try 'fastq-sanger', 'fastq-illumina' |
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 generatorRelated 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
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Questions about bio-format-conversion.
- Which coding agents can use bio-format-conversion?
- bio-format-conversion installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

