--> --- name: bio-read-sequences description: Read biological sequence files (FASTA, FASTQ, GenBank, EMBL, ABI, SFF) using Biopython Bio.SeqIO. Use when parsing sequence files, iterating multi-sequence files, random access to large files, or high-performance parsing. tool_type: python primary_tool: Bio.SeqIO measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Read biological sequence data from files us...
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---
name: bio-read-sequences
description: Read biological sequence files (FASTA, FASTQ, GenBank, EMBL, ABI, SFF) using Biopython Bio.SeqIO. Use when parsing sequence files, iterating multi-sequence files, random access to large files, or high-performance parsing.
tool_type: python
primary_tool: Bio.SeqIO
measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.
allowed-tools:
- read_file
- run_shell_command
---
# Read Sequences
Read biological sequence data from files using Biopython's Bio.SeqIO module.
## Required Import
```python
from Bio import SeqIO
```
## Core Functions
### SeqIO.parse() - Multiple Records (Iterator)
Use for files with one or more sequences. Returns an iterator of SeqRecord objects.
```python
for record in SeqIO.parse('sequences.fasta', 'fasta'):
print(record.id, len(record.seq))
```
**Important:** Always specify the format explicitly as the second argument.
### SeqIO.read() - Single Record Only
Use when file contains exactly one sequence. Raises error if zero or multiple records.
```python
record = SeqIO.read('single.fasta', 'fasta')
```
### SeqIO.to_dict() - Load All Into Memory
Use for random access by record ID. Loads entire file into memory.
```python
records = SeqIO.to_dict(SeqIO.parse('sequences.fasta', 'fasta'))
seq = records['sequence_id'].seq
```
### SeqIO.index() - Large File Random Access
Use for large files when you need random access without loading everything into memory.
```python
records = SeqIO.index('large.fasta', 'fasta')
seq = records['sequence_id'].seq
records.close()
```
### SeqIO.index_db() - SQLite-Backed Indexing
Use for very large files or multiple files. Creates persistent SQLite index.
```python
# Create index (first time - parses file)
records = SeqIO.index_db('index.sqlite', 'large.fasta', 'fasta')
seq = records['sequence_id'].seq
records.close()
# Reuse existing index (instant load)
records = SeqIO.index_db('index.sqlite')
# Index multiple files together
records = SeqIO.index_db('combined.sqlite', ['file1.fasta', 'file2.fasta'], 'fasta')
```
**Advantages over index():**
- Persistent index survives program restarts
- Can index multiple files as one database
- Lower memory for extremely large files
- SQLite file can be shared across processes
## High-Performance Parsing
For maximum throughput on large files, use low-level parsers (3-6x faster than SeqIO.parse):
### SimpleFastaParser
```python
from Bio.SeqIO.FastaIO import SimpleFastaParser
with open('large.fasta') as handle:
for title, sequence in SimpleFastaParser(handle):
if len(sequence) > 1000:
print(title.split()[0]) # First word is usually ID
```
Returns `(title, sequence)` tuples as strings (no SeqRecord overhead).
### FastqGeneralIterator
```python
from Bio.SeqIO.QualityIO import FastqGeneralIterator
with open('reads.fastq') as handle:
for title, sequence, quality in FastqGeneralIterator(handle):
avg_qual = sum(ord(c) - 33 for c in quality) / len(quality)
```
Returns `(title, sequence, quality_string)` tuples.
## Common Formats
| Format | String | Typical Extension | Notes |
|--------|--------|-------------------|-------|
| FASTA | `'fasta'` | .fasta, .fa, .fna, .faa | Most common |
| FASTA 2-line | `'fasta-2line'` | .fasta | One line per sequence (no wrapping) |
| FASTQ | `'fastq'` | .fastq, .fq | With quality scores |
| FASTQ Solexa | `'fastq-solexa'` | .fastq | Old Solexa/Illumina (pre-1.3) |
| FASTQ Illumina | `'fastq-illumina'` | .fastq | Illumina 1.3-1.7 |
| GenBank | `'genbank'` or `'gb'` | .gb, .gbk | With features/annotations |
| EMBL | `'embl'` | .embl | European format with features |
| Swiss-Prot | `'swiss'` | .dat | UniProt format |
## Specialized Formats
| Format | String | Use Case |
|--------|--------|----------|
| ABI | `'abi'` | Sanger sequencing trace files (.ab1) |
| ABI Trimmed | `'abi-trim'` | ABI with low-quality ends trimmed |
| SFF | `'sff'` | 454/Ion Torrent flowgram data |
| SFF Trimmed | `'sff-trim'` | SFF with adapter/quality trimming |
| QUAL | `'qual'` | Quality scores file (pairs with FASTA) |
| PHD | `'phd'` | Phred/Phrap/Consed output |
| ACE | `'ace'` | Assembly format (Consed) |
| PDB SEQRES | `'pdb-seqres'` | Protein sequences from PDB files |
| PDB ATOM | `'pdb-atom'` | Sequences from ATOM records in PDB |
| SnapGene | `'snapgene'` | SnapGene .dna files |
| GCK | `'gck'` | Gene Construction Kit files |
| XDNA | `'xdna'` | DNA Strider / SerialCloner files |
### Reading ABI Trace Files
```python
# Read Sanger sequencing trace with quality
record = SeqIO.read('sample.ab1', 'abi')
print(f'Sequence: {record.seq}')
qualities = record.letter_annotations['phred_quality']
# Auto-trim low quality ends
record_trimmed = SeqIO.read('sample.ab1', 'abi-trim')
```
### Reading 454/Ion Torrent SFF
```python
for record in SeqIO.parse('reads.sff', 'sff'):
print(record.id, len(record.seq))
# With trimming applied
for record in SeqIO.parse('reads.sff', 'sff-trim'):
print(record.id, len(record.seq))
```
### Reading PDB Sequences
```python
# Get sequences from SEQRES records
for record in SeqIO.parse('structure.pdb', 'pdb-seqres'):
print(f'Chain {record.id}: {record.seq}')
# Get sequences from ATOM coordinates
for record in SeqIO.parse('structure.pdb', 'pdb-atom'):
print(f'Chain {record.id}: {record.seq}')
```
## Alignment Formats (Read-Only)
| Format | String | Notes |
|--------|--------|-------|
| PHYLIP | `'phylip'` | Interleaved phylip |
| PHYLIP Sequential | `'phylip-sequential'` | Sequential phylip |
| PHYLIP Relaxed | `'phylip-relaxed'` | Longer names allowed |
| Clustal | `'clustal'` | ClustalW output |
| Stockholm | `'stockholm'` | Rfam/Pfam alignments |
| NEXUS | `'nexus'` | PAUP/MrBayes format |
| MAF | `'maf'` | Multiple Alignment Format |
## SeqRecord Object Attributes
After parsing, each record has these key attributes:
```python
record.id # Sequence identifier (string)
record.name # Sequence name (string)
record.description # Full description line (string)
record.seq # Sequence data (Seq object)
record.features # List of SeqFeature objects (GenBank/EMBL)
record.annotations # Dictionary of annotations
record.letter_annotations # Per-letter annotations (quality scores)
record.dbxrefs # Database cross-references
```
## Code Patterns
### Collect All Sequences Into a List
```python
records = list(SeqIO.parse('sequences.fasta', 'fasta'))
```
### Count Records Without Loading All
```python
count = sum(1 for _ in SeqIO.parse('sequences.fasta', 'fasta'))
```
### Fast Count (FASTA only)
```python
from Bio.SeqIO.FastaIO import SimpleFastaParser
with open('sequences.fasta') as f:
count = sum(1 for _ in SimpleFastaParser(f))
```
### Get Sequence IDs Only
```python
ids = [record.id for record in SeqIO.parse('sequences.fasta', 'fasta')]
```
### Read GenBank with Features
```python
for record in SeqIO.parse('sequence.gb', 'genbank'):
for feature in record.features:
if feature.type == 'CDS':
print(feature.qualifiers.get('product', ['Unknown'])[0])
cds_seq = feature.extract(record.seq) # Get feature sequence
```
### Access FASTQ Quality Scores
```python
for record in SeqIO.parse('reads.fastq', 'fastq'):
qualities = record.letter_annotations['phred_quality']
avg_quality = sum(qualities) / len(qualities)
```
### Read From File Handle
```python
with open('sequences.fasta', 'r') as handle:
for record in SeqIO.parse(handle, 'fasta'):
print(record.id)
```
### Custom ID Function for Indexing
```python
def get_accession(identifier):
return identifier.split('.')[0] # Remove version
records = SeqIO.index('sequences.fasta', 'fasta', key_function=get_accession)
```
## Common Errors
| Error | Cause | Solution |
|-------|-------|----------|
| `ValueError: More than one record` | Used `read()` on multi-record file | Use `parse()` instead |
| `ValueError: No records found` | Used `read()` on empty file | Check file exists and has content |
| `ValueError: unknown format` | Typo in format string | Check format string spelling |
| `UnicodeDecodeError` | Binary file or wrong encoding | Open with `encoding='latin-1'` or check file |
| `sqlite3.OperationalError` | index_db file locked | Close other connections first |
## Decision Tree
```
Need to read sequences?
├── Single record in file?
│ └── Use SeqIO.read()
├── Multiple records?
│ ├── Need all in memory at once?
│ │ └── Use list(SeqIO.parse()) or SeqIO.to_dict()
│ ├── Process one at a time (memory efficient)?
│ │ └── Use SeqIO.parse() iterator
│ ├── Large file, need random access by ID?
│ │ ├── Single session? → Use SeqIO.index()
│ │ └── Persistent/multi-file? → Use SeqIO.index_db()
│ └── Maximum throughput needed?
│ └── Use SimpleFastaParser or FastqGeneralIterator
├── Sanger sequencing trace?
│ └── Use 'abi' or 'abi-trim' format
├── 454/Ion Torrent data?
│ └── Use 'sff' or 'sff-trim' format
└── Protein from structure?
└── Use 'pdb-seqres' or 'pdb-atom' format
```
## Related Skills
- write-sequences - Write parsed sequences to new files
- filter-sequences - Filter sequences by criteria after reading
- format-conversion - Convert between formats
- compressed-files - Read gzip/bzip2/BGZF compressed sequence files
- sequence-manipulation/seq-objects - Work with parsed SeqRecord objects
- database-access - Fetch sequences from NCBI instead of local files
- alignment-files - For SAM/BAM/CRAM alignment files, use samtools/pysam
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