bio-genome-assembly-hifi-assembly

---
name: bio-genome-assembly-hifi-assembly
description: High-quality genome assembly from PacBio HiFi reads using hifiasm with phasing support. Use when building reference-quality diploid assemblies from HiFi data, especially with trio or Hi-C phasing for fully resolved haplotypes.
tool_type: cli
primary_tool: hifiasm
---

## Version Compatibility

Reference examples tested with: BUSCO 5.5+, QUAST 5.2+

Before using code patterns, verify installed versions match. If versions differ:
- Python: `pip show <package>` then `help(module.function)` to check signatures
- CLI: `<tool> --version` then `<tool> --help` to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.

# HiFi Assembly

**"Assemble a genome from HiFi reads"** → Build a phased, reference-quality diploid assembly from PacBio HiFi reads with optional trio or Hi-C phasing for full haplotype resolution.
- CLI: `hifiasm -o output reads.fq.gz`

## Basic Assembly

**Goal:** Produce a primary contig assembly from PacBio HiFi reads.

**Approach:** Run hifiasm with default parameters and convert GFA output to FASTA.

```bash
# Primary assembly (single haplotype consensus)
hifiasm -o output_prefix -t 32 reads.hifi.fastq.gz

# Output files:
# output_prefix.bp.p_ctg.gfa  - Primary contigs
# output_prefix.bp.a_ctg.gfa  - Alternate contigs
# output_prefix.bp.hap1.p_ctg.gfa - Haplotype 1 (if phased)
# output_prefix.bp.hap2.p_ctg.gfa - Haplotype 2 (if phased)

# Convert GFA to FASTA
awk '/^S/{print ">"$2;print $3}' output_prefix.bp.p_ctg.gfa > assembly.fasta
```

## Trio-Binned Phasing

**Goal:** Generate fully phased haplotype assemblies using parental short-read data.

**Approach:** Build k-mer databases from parental reads with yak, then supply them to hifiasm for trio binning.

```bash
# With parental short reads for trio binning
hifiasm -o trio_asm -t 32 \
    -1 paternal.yak \
    -2 maternal.yak \
    child.hifi.fastq.gz

# Create yak databases from parental Illumina reads first
yak count -b37 -t16 -o paternal.yak paternal_R1.fq.gz paternal_R2.fq.gz
yak count -b37 -t16 -o maternal.yak maternal_R1.fq.gz maternal_R2.fq.gz
```

## Hi-C Phasing

**Goal:** Phase haplotypes without parental data using chromatin proximity.

**Approach:** Supply Hi-C paired-end reads to hifiasm for contact-based haplotype resolution.

```bash
# Use Hi-C reads for phasing (no parents needed)
hifiasm -o hic_asm -t 32 \
    --h1 hic_R1.fastq.gz \
    --h2 hic_R2.fastq.gz \
    reads.hifi.fastq.gz

# Produces fully phased hap1 and hap2 assemblies
```

## Key Parameters

| Parameter | Default | Description |
|-----------|---------|-------------|
| -t | 1 | Threads |
| -l | 0 | Purge level (0=none, 1=light, 2=aggressive) |
| -s | 0.55 | Similarity threshold for duplicate detection |
| --primary | - | Output primary contigs only (no alternates) |
| --n-hap | 2 | Expected number of haplotypes |
| -D | 5.0 | Drop reads with depth > D*average |
| -N | 100 | Consider up to N overlaps for each read |

## Purge Duplicates

**Goal:** Control haplotype duplication levels in the primary assembly.

**Approach:** Adjust the hifiasm purge level parameter based on sample heterozygosity.

```bash
# Aggressive purging for high heterozygosity
hifiasm -o asm -t 32 -l 2 reads.hifi.fastq.gz

# Minimal purging for inbred samples
hifiasm -o asm -t 32 -l 0 reads.hifi.fastq.gz
```

## Ultra-Long ONT Integration

**Goal:** Improve contiguity across complex repeats by supplementing HiFi with ultra-long ONT reads.

**Approach:** Supply ONT reads via the --ul flag to span regions that HiFi reads alone cannot resolve.

```bash
# Combine HiFi accuracy with ONT length
hifiasm -o hybrid_asm -t 32 \
    --ul ont_ultralong.fastq.gz \
    hifi_reads.fastq.gz

# UL reads help span complex repeats
```

## Assembly Stats

**Goal:** Evaluate assembly contiguity, completeness, and correctness.

**Approach:** Compute summary statistics with seqkit/assembly-stats, run QUAST for contiguity metrics, and BUSCO for gene completeness.

```bash
# Quick stats with seqkit
seqkit stats assembly.fasta

# Detailed with assembly-stats
assembly-stats assembly.fasta

# QUAST assessment
quast.py -o quast_output assembly.fasta

# BUSCO completeness
busco -i assembly.fasta -l mammalia_odb10 -o busco_out -m genome
```

## Memory and Runtime

| Genome Size | HiFi Coverage | RAM | Time (32 cores) |
|-------------|---------------|-----|-----------------|
| 3 Gb | 30x | ~200 GB | 12-24 hours |
| 3 Gb | 60x | ~400 GB | 24-48 hours |
| 500 Mb | 40x | ~64 GB | 2-4 hours |

## Python Wrapper

**Goal:** Provide a reusable Python interface for running hifiasm with various phasing modes.

**Approach:** Wrap the hifiasm CLI call with optional Hi-C and ultra-long ONT parameters, then convert GFA output to FASTA.

```python
import subprocess
from pathlib import Path

def run_hifiasm(hifi_reads, output_prefix, threads=32, purge_level=0,
                hic_r1=None, hic_r2=None, ul_reads=None):
    cmd = ['hifiasm', '-o', output_prefix, '-t', str(threads), '-l', str(purge_level)]

    if hic_r1 and hic_r2:
        cmd.extend(['--h1', hic_r1, '--h2', hic_r2])

    if ul_reads:
        cmd.extend(['--ul', ul_reads])

    cmd.append(hifi_reads)
    subprocess.run(cmd, check=True)

    gfa = Path(f'{output_prefix}.bp.p_ctg.gfa')
    fasta = Path(f'{output_prefix}.fasta')

    with open(fasta, 'w') as out:
        with open(gfa) as f:
            for line in f:
                if line.startswith('S'):
                    parts = line.strip().split('\t')
                    out.write(f'>{parts[1]}\n{parts[2]}\n')

    return fasta

# Example
assembly = run_hifiasm('sample.hifi.fq.gz', 'sample_asm', threads=48, hic_r1='hic_R1.fq.gz', hic_r2='hic_R2.fq.gz')
```

## Troubleshooting

| Issue | Solution |
|-------|----------|
| High duplication | Increase purge level (-l 2) |
| Missing haplotypes | Add Hi-C or trio data for phasing |
| Memory errors | Reduce -D parameter or downsample reads |
| Fragmented assembly | Check read quality; consider UL ONT addition |

## Related Skills

- genome-assembly/assembly-qc - QUAST and BUSCO
- genome-assembly/scaffolding - YaHS Hi-C scaffolding
- genome-assembly/contamination-detection - CheckM2 decontamination
- long-read-sequencing/read-qc - HiFi quality control