본문으로 건너뛰기
cccskills
무료GitHub에 공개

bio-format-conversion

Convert biological sequence files between FASTA, FASTQ, GenBank, and EMBL using Biopython. Handle required annotations, process multiple files, and identify when conversion discards information such as sequence quality scores or annotated biological features.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Convert between sequence file formats (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO. Use when changing file formats or preparing data for different tools.

설치 방법 보기

이럴 때 유용합니다

  • Converting GenBank files to FASTA
  • Preparing sequence files for another analysis tool
  • Batch converting files in a directory
  • Adding required annotations before conversion

포함된 파일(3)

  • SKILL.md5.8 KB
  • examples/convert_format.py1.6 KB
  • usage-guide.md1.1 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

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

FromToNotes
GenBankFASTALoses annotations, keeps sequence
FASTAGenBankNeed to add molecule_type
FASTQFASTALoses quality scores
FASTAFASTQNeed to add quality scores
GenBankEMBLUsually works directly
StockholmFASTAAlignment 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

ErrorCauseSolution
ValueError: missing molecule_typeFASTA to GenBankAdd molecule_type annotation
ValueError: missing quality scoresFASTA to FASTQAdd phred_quality to letter_annotations
KeyError: 'phred_quality'Wrong FASTQ variantTry '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 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

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

adaptyv

무료

Support protein design with cloud laboratory testing for binding, expression, thermal stability, and enzyme activity. Covers sequence optimization, submitting experiments through the Adaptyv API, checking progress, and downloading experimental results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Validate designed proteins with laboratory assays
  • Screen and redesign sequences for better solubility
  • Submit protein testing experiments through an API
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

Build flexible daily plans that account for ADHD-related difficulties with time estimation and getting started. Narrow priorities to three tasks, add transition buffers, and choose small next actions that match the energy available that day.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Choosing three priorities for today
  • Planning a schedule with transition buffers
  • Finding a small first step when starting feels difficult
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

aeon

무료

Build Python workflows for data recorded over time, including classification, forecasting, anomaly detection, and pattern search. Using aeon, the skill guides preprocessing, algorithm selection, feature extraction, and evaluation through interfaces compatible with scikit-learn.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Classify time series by their patterns
  • Forecast future values from historical data
  • Detect anomalies and change points
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

Use a browser to research topics, extract page information, fill forms, and test websites. Guides agents through identifying page controls, interacting with web apps, saving screenshots or PDFs, and reusing saved login sessions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Researching topics and reading web articles
  • Filling and submitting online forms
  • Extracting page text and links
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

Combine health measurements, exercise, sleep, nutrition, and mental health records to examine trends, unusual changes, and estimated risks. The skill produces personalized suggestions and text or interactive HTML reports using local data without external API calls.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Review health records together in a comprehensive report
  • Explore links between sleep, mood, exercise, and weight
  • Summarize estimated disease and nutrition risks
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

alphafold

무료

Predict structures for designed protein sequences and protein complexes with AlphaFold2 or ColabFold. Inspect structure files and confidence scores to assess folding and chain interfaces, with guidance for local runs, Modal execution, and common prediction errors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Check predicted folding of a designed protein sequence
  • Predict a binder–target protein complex
  • Review structure and interface confidence scores
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

FreedomIntelligence의 스킬 모두 보기

이 스킬의 문제 신고