bio-compressed-files
$
npx mdskill add GPTomics/bioSkills/bio-compressed-filesRead and write compressed biosequence files using Biopython
- Parse sequence data from .gz, .bz2, and BGZF files without decompressing to disk
- Uses Python stdlib gzip/bz2 and Biopython's BGZF for file access
- Chooses appropriate decompression method based on file extension and format
- Returns SeqIO-compatible file handles for downstream processing
SKILL.md
.github/skills/bio-compressed-filesView on GitHub ↗
---
name: bio-compressed-files
description: Read and write compressed sequence files (gzip, bzip2, BGZF) using Biopython. Use when working with .gz or .bz2 sequence files. Use BGZF for indexable compressed files.
tool_type: python
primary_tool: Bio.bgzf
---
## 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.
# Compressed Files
Handle gzip, bzip2, and BGZF compressed sequence files with Biopython.
**"Read a compressed sequence file"** → Open a compressed file handle in text mode, then parse with the standard SeqIO interface.
- gzip: `gzip.open(path, 'rt')` (Python stdlib)
- bzip2: `bz2.open(path, 'rt')` (Python stdlib)
- BGZF: `bgzf.open(path, 'rt')` (BioPython) or direct `SeqIO.parse(path, fmt)`
**"Make a compressed file indexable"** → Convert to BGZF format. Only BGZF supports `SeqIO.index()` on compressed data.
## Required Imports
```python
import gzip
import bz2
from Bio import SeqIO
from Bio import bgzf
```
## Reading Compressed Files
**Goal:** Parse sequence records from compressed files without decompressing to disk.
**Approach:** Open a decompression handle in text mode (`'rt'`), then pass the handle to `SeqIO.parse()`. The parser works identically to uncompressed input.
### Gzip (.gz) (BioPython 1.83+)
```python
with gzip.open('sequences.fasta.gz', 'rt') as handle:
for record in SeqIO.parse(handle, 'fasta'):
print(record.id, len(record.seq))
```
**Important:** Use `'rt'` (read text) mode, not `'rb'` (read binary).
### Bzip2 (.bz2) (BioPython 1.83+)
```python
with bz2.open('sequences.fasta.bz2', 'rt') as handle:
for record in SeqIO.parse(handle, 'fasta'):
print(record.id, len(record.seq))
```
### BGZF (Block Gzip) (BioPython 1.83+)
BGZF files can be read like regular gzip, but also support indexing:
```python
for record in SeqIO.parse('sequences.fasta.bgz', 'fasta'):
print(record.id)
with bgzf.open('sequences.fasta.bgz', 'rt') as handle:
for record in SeqIO.parse(handle, 'fasta'):
print(record.id)
```
## Writing Compressed Files
**Goal:** Save sequence records directly to compressed files without an intermediate uncompressed step.
**Approach:** Open a compression handle in text mode (`'wt'`), then pass it to `SeqIO.write()`.
### Gzip (.gz)
```python
with gzip.open('output.fasta.gz', 'wt') as handle:
SeqIO.write(records, handle, 'fasta')
```
### Bzip2 (.bz2)
```python
with bz2.open('output.fasta.bz2', 'wt') as handle:
SeqIO.write(records, handle, 'fasta')
```
### BGZF (.bgz)
```python
with bgzf.open('output.fasta.bgz', 'wt') as handle:
SeqIO.write(records, handle, 'fasta')
```
## BGZF: Indexable Compression
**Goal:** Enable random access to records in compressed sequence files.
**Approach:** Write sequences in BGZF (Block GZip Format) — the only compressed format supporting `SeqIO.index()` and `SeqIO.index_db()`. BGZF is a gzip variant used by BAM and tabix-indexed files.
### Create Indexable Compressed File
```python
from Bio import SeqIO, bgzf
records = SeqIO.parse('input.fasta', 'fasta')
with bgzf.open('output.fasta.bgz', 'wt') as handle:
SeqIO.write(records, handle, 'fasta')
```
### Index a BGZF File
```python
records = SeqIO.index('sequences.fasta.bgz', 'fasta')
seq = records['target_id'].seq
records.close()
records = SeqIO.index_db('index.sqlite', 'sequences.fasta.bgz', 'fasta')
```
### Convert Gzip to BGZF
**"Convert gzip to indexable format"** → Parse from gzip handle, write through BGZF handle.
```python
from Bio import SeqIO, bgzf
import gzip
with gzip.open('input.fasta.gz', 'rt') as in_handle:
with bgzf.open('output.fasta.bgz', 'wt') as out_handle:
SeqIO.write(SeqIO.parse(in_handle, 'fasta'), out_handle, 'fasta')
```
## Code Patterns
### Read Gzipped FASTQ
```python
with gzip.open('reads.fastq.gz', 'rt') as handle:
records = list(SeqIO.parse(handle, 'fastq'))
print(f'Loaded {len(records)} reads')
```
### Count Records in Gzipped File
```python
with gzip.open('sequences.fasta.gz', 'rt') as handle:
count = sum(1 for _ in SeqIO.parse(handle, 'fasta'))
print(f'{count} sequences')
```
### Fast Count with Low-Level Parser
```python
from Bio.SeqIO.FastaIO import SimpleFastaParser
import gzip
with gzip.open('sequences.fasta.gz', 'rt') as handle:
count = sum(1 for _ in SimpleFastaParser(handle))
```
### Convert Compressed to Uncompressed
```python
with gzip.open('input.fasta.gz', 'rt') as in_handle:
records = SeqIO.parse(in_handle, 'fasta')
SeqIO.write(records, 'output.fasta', 'fasta')
```
### Convert Uncompressed to Compressed
```python
records = SeqIO.parse('input.fasta', 'fasta')
with gzip.open('output.fasta.gz', 'wt') as out_handle:
SeqIO.write(records, out_handle, 'fasta')
```
### Auto-Detect Compression
```python
from pathlib import Path
from Bio import SeqIO, bgzf
import gzip
import bz2
def open_sequence_file(filepath, format):
filepath = Path(filepath)
suffix = filepath.suffix.lower()
if suffix == '.gz':
# Could be gzip or bgzf - bgzf handles both
handle = bgzf.open(filepath, 'rt')
elif suffix == '.bgz':
handle = bgzf.open(filepath, 'rt')
elif suffix == '.bz2':
handle = bz2.open(filepath, 'rt')
else:
handle = open(filepath, 'r')
return SeqIO.parse(handle, format)
```
### Process Large Gzipped File (Memory Efficient)
```python
with gzip.open('large.fastq.gz', 'rt') as handle:
for record in SeqIO.parse(handle, 'fastq'):
if len(record.seq) >= 100:
process(record)
```
### Compress Existing File (Raw Copy)
```python
import shutil
with open('sequences.fasta', 'rb') as f_in:
with gzip.open('sequences.fasta.gz', 'wb') as f_out:
shutil.copyfileobj(f_in, f_out)
```
## Compression Comparison
| Format | Extension | Indexable | Speed | Compression |
|--------|-----------|-----------|-------|-------------|
| Gzip | `.gz` | No | Fast | Good |
| BGZF | `.bgz` | **Yes** | Fast | Good |
| Bzip2 | `.bz2` | No | Slow | Better |
| LZMA | `.xz` | No | Slowest | Best |
## When to Use Each Format
| Use Case | Recommended Format |
|----------|-------------------|
| Archive (no random access needed) | gzip or bzip2 |
| Need to index compressed file | **BGZF** |
| BAM files and tabix | BGZF (native) |
| Maximum compression | bzip2 or xz |
| Best speed | gzip or BGZF |
## Common Errors
| Error | Cause | Solution |
|-------|-------|----------|
| `TypeError: a bytes-like object is required` | Used 'rb' mode | Use 'rt' for text mode |
| `UnicodeDecodeError` | Wrong encoding | Try `gzip.open(file, 'rt', encoding='latin-1')` |
| `gzip.BadGzipFile` | Not a gzip file | Check file extension matches actual format |
| `OSError: Not a gzipped file` | Corrupt or wrong format | Verify file integrity |
| `SeqIO.index() fails on .gz` | Regular gzip not indexable | Convert to BGZF first |
## Decision Tree
```
Working with compressed sequence files?
├── Just reading sequentially?
│ └── Use gzip.open() or bz2.open() with 'rt' mode
├── Need to index the compressed file?
│ └── Convert to BGZF, then use SeqIO.index()
├── Writing compressed output?
│ ├── Will need to index later? → Use bgzf.open()
│ └── Just archiving? → Use gzip.open() or bz2.open()
└── Converting between formats?
└── Parse with SeqIO, write to new handle
```
## Related Skills
- read-sequences - Core parsing functions used with compressed handles
- write-sequences - Write to compressed output files
- batch-processing - Process multiple compressed files
- alignment-files - BAM files use BGZF natively; samtools handles compression
More from GPTomics/bioSkills
- bio-admet-predictionPredicts ADMET properties using ADMETlab 3.0 API or DeepChem models. Estimates bioavailability, CYP inhibition, hERG liability, and 119 toxicity endpoints with uncertainty quantification. Filters for PAINS and other structural alerts. Use when filtering compounds for drug-likeness or prioritizing leads by predicted safety.
- bio-alignment-amplicon-clippingTrim PCR primers from aligned reads in amplicon-panel BAMs using samtools ampliconclip. Use when processing SARS-CoV-2 ARTIC, hereditary cancer panels, ctDNA hot-spot panels, or any amplicon assay where primer-derived bases would falsely confirm reference at primer footprints.
- bio-alignment-filteringFilter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific reads, removing low-quality alignments, or subsetting to target regions.
- bio-alignment-indexingCreate and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific genomic regions.
- bio-alignment-ioRead, 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.
- bio-alignment-msa-parsingParse and analyze multiple sequence alignments using Biopython. Extract sequences, identify conserved regions, analyze gaps, work with annotations, and manipulate alignment data for downstream analysis. Use when parsing or manipulating multiple sequence alignments.
- bio-alignment-msa-statisticsCalculate alignment statistics including sequence identity, conservation scores, substitution matrices, and similarity metrics. Use when comparing alignment quality, measuring sequence divergence, and analyzing evolutionary patterns.
- bio-alignment-multiplePerform multiple sequence alignment using MAFFT, MUSCLE5, ClustalOmega, or T-Coffee. Guides tool and algorithm selection based on dataset size, sequence divergence, and downstream application. Use when aligning three or more homologous sequences for phylogenetics, conservation analysis, or evolutionary studies.
- bio-alignment-pairwisePerform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner. Use when comparing two sequences, finding optimal alignments, scoring similarity, and identifying local or global matches between DNA, RNA, or protein sequences.
- bio-alignment-sortingSort alignment files by coordinate or read name using samtools and pysam. Use when preparing BAM files for indexing, variant calling, or paired-end analysis.