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paired-end-fastq skill

/sequence-io/paired-end-fastq

This skill helps you manage paired-end FASTQ data with Biopython by synchronizing, filtering, interleaving, and auto-detecting R1/R2 pairs.

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---
name: bio-paired-end-fastq
description: Handle paired-end FASTQ files (R1/R2) using Biopython. Use when working with Illumina paired reads, synchronizing pairs, interleaving/deinterleaving, or filtering paired data.
tool_type: python
primary_tool: Bio.SeqIO
---

## 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.

# Paired-End FASTQ

**"Work with my paired-end FASTQ files"** → Iterate R1/R2 pairs in sync, filter both mates together, interleave/deinterleave files, and auto-detect paired file naming.
- Python: `SeqIO.parse()` with `zip()` iteration (BioPython)

Handle paired-end sequencing data (R1/R2 files) using Biopython.

## Required Import

```python
from Bio import SeqIO
```

## Paired File Naming Conventions

Common patterns for paired files:
- `sample_R1.fastq` / `sample_R2.fastq`
- `sample_1.fastq` / `sample_2.fastq`
- `sample_R1_001.fastq` / `sample_R2_001.fastq`

## Iterate Pairs Together

### Basic Paired Iteration
```python
r1_records = SeqIO.parse('reads_R1.fastq', 'fastq')
r2_records = SeqIO.parse('reads_R2.fastq', 'fastq')

for r1, r2 in zip(r1_records, r2_records):
    print(f'R1: {r1.id}, R2: {r2.id}')
    print(f'Lengths: {len(r1.seq)}, {len(r2.seq)}')
```

### Verify Pair Matching
```python
def iterate_pairs(r1_file, r2_file, format='fastq'):
    r1_records = SeqIO.parse(r1_file, format)
    r2_records = SeqIO.parse(r2_file, format)

    for r1, r2 in zip(r1_records, r2_records):
        # Strip /1, /2 or .1, .2 suffixes for comparison
        r1_base = r1.id.rsplit('/', 1)[0].rsplit('.', 1)[0]
        r2_base = r2.id.rsplit('/', 1)[0].rsplit('.', 1)[0]
        if r1_base != r2_base:
            raise ValueError(f'Pair mismatch: {r1.id} vs {r2.id}')
        yield r1, r2

for r1, r2 in iterate_pairs('reads_R1.fastq', 'reads_R2.fastq'):
    process_pair(r1, r2)
```

## Filter Pairs Together

### Filter by Quality (Both Must Pass)
```python
def filter_pairs_by_quality(r1_file, r2_file, min_avg_qual=25):
    r1_records = SeqIO.parse(r1_file, 'fastq')
    r2_records = SeqIO.parse(r2_file, 'fastq')

    r1_passed, r2_passed = [], []
    for r1, r2 in zip(r1_records, r2_records):
        q1 = sum(r1.letter_annotations['phred_quality']) / len(r1.seq)
        q2 = sum(r2.letter_annotations['phred_quality']) / len(r2.seq)
        if q1 >= min_avg_qual and q2 >= min_avg_qual:
            r1_passed.append(r1)
            r2_passed.append(r2)

    return r1_passed, r2_passed

r1_good, r2_good = filter_pairs_by_quality('reads_R1.fastq', 'reads_R2.fastq')
SeqIO.write(r1_good, 'filtered_R1.fastq', 'fastq')
SeqIO.write(r2_good, 'filtered_R2.fastq', 'fastq')
```

### Filter by Length (Both Must Pass)
```python
def filter_pairs_by_length(r1_file, r2_file, min_length=50):
    r1_records = SeqIO.parse(r1_file, 'fastq')
    r2_records = SeqIO.parse(r2_file, 'fastq')

    r1_passed, r2_passed = [], []
    for r1, r2 in zip(r1_records, r2_records):
        if len(r1.seq) >= min_length and len(r2.seq) >= min_length:
            r1_passed.append(r1)
            r2_passed.append(r2)

    return r1_passed, r2_passed
```

### Memory-Efficient Paired Filtering

**Goal:** Quality-filter paired reads while maintaining R1/R2 synchronization without loading all reads into memory.

**Approach:** Stream both files in lockstep with `zip`, evaluate both mates, and write only pairs where both pass.

**Reference (BioPython 1.83+):**
```python
def filter_pairs_streaming(r1_in, r2_in, r1_out, r2_out, min_qual=25):
    r1_records = SeqIO.parse(r1_in, 'fastq')
    r2_records = SeqIO.parse(r2_in, 'fastq')

    with open(r1_out, 'w') as r1_handle, open(r2_out, 'w') as r2_handle:
        passed = 0
        for r1, r2 in zip(r1_records, r2_records):
            q1 = sum(r1.letter_annotations['phred_quality']) / len(r1.seq)
            q2 = sum(r2.letter_annotations['phred_quality']) / len(r2.seq)
            if q1 >= min_qual and q2 >= min_qual:
                SeqIO.write(r1, r1_handle, 'fastq')
                SeqIO.write(r2, r2_handle, 'fastq')
                passed += 1
    return passed

count = filter_pairs_streaming('R1.fastq', 'R2.fastq', 'R1_filt.fastq', 'R2_filt.fastq')
print(f'{count} pairs passed filtering')
```

## Interleave Pairs

### Create Interleaved File

**Goal:** Merge separate R1/R2 files into a single interleaved file (R1, R2, R1, R2, ...).

**Approach:** Zip both iterators together and yield alternating records through a generator.

**Reference (BioPython 1.83+):**
```python
def interleave_pairs(r1_file, r2_file, output_file, format='fastq'):
    r1_records = SeqIO.parse(r1_file, format)
    r2_records = SeqIO.parse(r2_file, format)

    def interleaved():
        for r1, r2 in zip(r1_records, r2_records):
            yield r1
            yield r2

    count = SeqIO.write(interleaved(), output_file, format)
    return count // 2  # Return number of pairs

pairs = interleave_pairs('reads_R1.fastq', 'reads_R2.fastq', 'reads_interleaved.fastq')
print(f'Interleaved {pairs} pairs')
```

### Interleave with Modified IDs
```python
def interleave_with_suffix(r1_file, r2_file, output_file):
    r1_records = SeqIO.parse(r1_file, 'fastq')
    r2_records = SeqIO.parse(r2_file, 'fastq')

    def interleaved():
        for r1, r2 in zip(r1_records, r2_records):
            r1.id = f'{r1.id}/1'
            r1.description = ''
            r2.id = f'{r2.id}/2'
            r2.description = ''
            yield r1
            yield r2

    SeqIO.write(interleaved(), output_file, 'fastq')
```

## Deinterleave

### Split Interleaved to Paired Files
```python
def deinterleave(interleaved_file, r1_file, r2_file, format='fastq'):
    records = SeqIO.parse(interleaved_file, format)

    r1_records = []
    r2_records = []
    for i, record in enumerate(records):
        if i % 2 == 0:
            r1_records.append(record)
        else:
            r2_records.append(record)

    SeqIO.write(r1_records, r1_file, format)
    SeqIO.write(r2_records, r2_file, format)
    return len(r1_records)

pairs = deinterleave('interleaved.fastq', 'R1.fastq', 'R2.fastq')
print(f'Deinterleaved {pairs} pairs')
```

### Memory-Efficient Deinterleave
```python
def deinterleave_streaming(interleaved_file, r1_file, r2_file, format='fastq'):
    records = SeqIO.parse(interleaved_file, format)

    with open(r1_file, 'w') as r1_h, open(r2_file, 'w') as r2_h:
        pairs = 0
        for i, record in enumerate(records):
            if i % 2 == 0:
                SeqIO.write(record, r1_h, format)
            else:
                SeqIO.write(record, r2_h, format)
                pairs += 1
    return pairs
```

## Paired Statistics

### Count and Verify Pairs
```python
def paired_stats(r1_file, r2_file):
    r1_count = sum(1 for _ in SeqIO.parse(r1_file, 'fastq'))
    r2_count = sum(1 for _ in SeqIO.parse(r2_file, 'fastq'))

    if r1_count != r2_count:
        print(f'WARNING: Unequal counts! R1={r1_count}, R2={r2_count}')
    else:
        print(f'Pairs: {r1_count}')
        print(f'Total reads: {r1_count * 2}')

    return r1_count, r2_count

paired_stats('reads_R1.fastq', 'reads_R2.fastq')
```

### Paired Quality Summary
```python
def paired_quality_summary(r1_file, r2_file):
    r1_quals, r2_quals = [], []

    r1_records = SeqIO.parse(r1_file, 'fastq')
    r2_records = SeqIO.parse(r2_file, 'fastq')

    for r1, r2 in zip(r1_records, r2_records):
        r1_quals.append(sum(r1.letter_annotations['phred_quality']) / len(r1.seq))
        r2_quals.append(sum(r2.letter_annotations['phred_quality']) / len(r2.seq))

    print(f'R1 mean quality: {sum(r1_quals)/len(r1_quals):.1f}')
    print(f'R2 mean quality: {sum(r2_quals)/len(r2_quals):.1f}')

paired_quality_summary('reads_R1.fastq', 'reads_R2.fastq')
```

## Find Paired Files

### Auto-Detect Pair from R1
```python
from pathlib import Path

def find_r2(r1_path):
    r1_path = Path(r1_path)
    name = r1_path.name

    # Try common patterns
    patterns = [
        ('_R1', '_R2'),
        ('_1', '_2'),
        ('_R1_', '_R2_'),
        ('.R1.', '.R2.'),
    ]

    for p1, p2 in patterns:
        if p1 in name:
            r2_name = name.replace(p1, p2, 1)
            r2_path = r1_path.parent / r2_name
            if r2_path.exists():
                return r2_path

    return None

r2_file = find_r2('sample_R1.fastq')
if r2_file:
    print(f'Found pair: {r2_file}')
```

### Find All Paired Files in Directory
```python
from pathlib import Path

def find_all_pairs(directory, r1_pattern='*_R1*.fastq*'):
    pairs = []
    for r1_file in Path(directory).glob(r1_pattern):
        r2_file = find_r2(r1_file)
        if r2_file:
            pairs.append((r1_file, r2_file))
    return pairs

pairs = find_all_pairs('data/')
for r1, r2 in pairs:
    print(f'{r1.name} <-> {r2.name}')
```

## Compressed Paired Files

### Handle Gzipped Pairs
```python
import gzip

def iterate_gzipped_pairs(r1_gz, r2_gz):
    with gzip.open(r1_gz, 'rt') as r1_h, gzip.open(r2_gz, 'rt') as r2_h:
        r1_records = SeqIO.parse(r1_h, 'fastq')
        r2_records = SeqIO.parse(r2_h, 'fastq')
        for r1, r2 in zip(r1_records, r2_records):
            yield r1, r2

for r1, r2 in iterate_gzipped_pairs('reads_R1.fastq.gz', 'reads_R2.fastq.gz'):
    print(r1.id, r2.id)
```

## Common Errors

| Error | Cause | Solution |
|-------|-------|----------|
| Pair count mismatch | Files out of sync | Re-download or repair files |
| ID mismatch | Wrong file pairing | Check file naming conventions |
| Memory error | Large files loaded to list | Use streaming/generator approach |
| Missing R2 | Wrong naming pattern | Check `find_r2()` patterns |

## Related Skills

- read-sequences - Parse individual FASTQ files
- fastq-quality - Quality filtering before paired processing
- filter-sequences - Additional filtering criteria
- compressed-files - Handle gzipped paired files
- alignment-files - After filtering, align paired reads with bwa mem; proper pairs in BAM

Overview

This skill provides practical utilities for handling Illumina paired-end FASTQ files (R1/R2) using Biopython. It focuses on synchronized iteration, paired filtering, interleaving/deinterleaving, auto-detecting mate filenames, and support for gzipped inputs. Examples are memory-conscious and tested against BioPython 1.83+ patterns.

How this skill works

The code uses Bio.SeqIO.parse() to stream records from R1 and R2 in lockstep via zip(), verifying and synchronizing pair IDs. It includes streaming filter routines that only write pairs where both mates pass quality or length checks, generators for interleaving, and streaming deinterleaving to avoid loading all reads into memory. Helper functions detect common R1/R2 naming conventions and handle gzipped files with gzip.open().

When to use it

  • You have Illumina paired-end FASTQ files and need to keep mates synchronized while processing.
  • Filtering paired reads by quality or length where both mates must pass.
  • Converting separate R1/R2 files to an interleaved file for tools that expect interleaved input.
  • Splitting an interleaved FASTQ into separate R1 and R2 outputs without high memory use.
  • Auto-detecting or locating missing mate files in bulk directories.

Best practices

  • Stream records (SeqIO.parse + zip) to avoid memory spikes on large datasets.
  • Always verify pair identity (strip /1,/2 or .1,.2 suffixes) before assuming mates match.
  • Write filters so both mates must pass; otherwise downstream alignment or analysis may fail.
  • Prefer gzip.open('rt') for compressed inputs and keep output compression consistent with downstream tools.
  • Test examples on a small subset to confirm API signatures if your Biopython version differs.

Example use cases

  • Iterate R1/R2 in sync and compute mean paired quality for quality reporting.
  • Memory-efficient quality filter that writes only pairs passing a minimum average phred score to new R1/R2 files.
  • Interleave two separate FASTQ files into a single interleaved FASTQ for downstream tools.
  • Deinterleave an interleaved FASTQ stream into two output files without storing all reads in memory.
  • Locate missing R2 mates across a sequencing run directory using common naming patterns.

FAQ

What if R1 and R2 counts differ?

Count mismatch usually indicates file corruption, truncation, or wrong pairing. Recount, inspect headers for ID mismatches, and re-download or repair files before processing.

How do I handle compressed FASTQ files?

Open gzipped files with gzip.open(path,'rt') and pass the file handle to SeqIO.parse so parsing stays streaming and memory-efficient.