bio-workflows-genome-assembly-pipeline
$
npx mdskill add GPTomics/bioSkills/bio-workflows-genome-assembly-pipelineOrchestrates end-to-end genome assembly from raw reads to polished output.
- Handles short, long, and hybrid read sequencing data types.
- Integrates Fastp, SPAdes, Flye, Medaka, Pilon, BlobToolKit, QUAST, and BUSCO.
- Executes sequential steps including QC, assembly, polishing, and contamination checks.
- Delivers quality metrics like N50, BUSCO completeness, and error reduction rates.
SKILL.md
.github/skills/bio-workflows-genome-assembly-pipelineView on GitHub ↗
---
name: bio-workflows-genome-assembly-pipeline
description: End-to-end genome assembly workflow from reads to polished assembly with QC. Supports short reads (SPAdes), long reads (Flye), and hybrid approaches. Use when assembling genomes from raw reads.
tool_type: cli
primary_tool: Flye
workflow: true
depends_on:
- read-qc/fastp-workflow
- genome-assembly/short-read-assembly
- genome-assembly/long-read-assembly
- genome-assembly/assembly-polishing
- genome-assembly/assembly-qc
qc_checkpoints:
- after_assembly: "N50 reasonable, total length matches expected"
- after_polishing: "Error rate reduced, QV improved"
- after_busco: "Complete BUSCOs >90%"
---
## Version Compatibility
Reference examples tested with: BUSCO 5.5+, BWA 0.7.17+, Flye 2.9+, QUAST 5.2+, SPAdes 3.15+, fastp 0.23+, samtools 1.19+
Before using code patterns, verify installed versions match. If versions differ:
- 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.
# Genome Assembly Pipeline
**"Assemble and polish a genome from my sequencing reads"** → Orchestrate read QC, assembly (hifiasm, Flye, SPAdes), polishing (Medaka, Pilon), scaffolding, contamination detection (BlobToolKit), and quality assessment (QUAST, BUSCO).
Complete workflow from sequencing reads to polished, quality-assessed genome assembly.
## Workflow Overview
```
Reads (short and/or long)
|
v
[1. QC & Filtering] -----> fastp, NanoPlot
|
v
[2. Assembly] -----------> SPAdes (short) or Flye (long)
|
v
[3. Polishing] ----------> Pilon (short) or medaka (long)
|
v
[4. QC Assessment] ------> QUAST, BUSCO
|
v
Final polished assembly
```
## Path A: Short-Read Assembly (SPAdes)
### Step 1: QC
```bash
fastp -i reads_R1.fastq.gz -I reads_R2.fastq.gz \
-o trimmed_R1.fq.gz -O trimmed_R2.fq.gz \
--detect_adapter_for_pe \
--qualified_quality_phred 20 \
--length_required 50 \
--html qc_report.html
```
### Step 2: Assembly with SPAdes
```bash
# Standard bacterial assembly
spades.py \
-1 trimmed_R1.fq.gz \
-2 trimmed_R2.fq.gz \
-o spades_output \
--careful \
-t 16 \
-m 64
# For isolate genomes
spades.py --isolate \
-1 trimmed_R1.fq.gz \
-2 trimmed_R2.fq.gz \
-o spades_output \
-t 16
```
### Step 3: Polishing with Pilon
```bash
# Align reads to assembly
bwa index spades_output/scaffolds.fasta
bwa mem -t 16 spades_output/scaffolds.fasta \
trimmed_R1.fq.gz trimmed_R2.fq.gz | \
samtools sort -@ 4 -o aligned.bam
samtools index aligned.bam
# Polish
pilon --genome spades_output/scaffolds.fasta \
--frags aligned.bam \
--output polished \
--threads 16
```
## Path B: Long-Read Assembly (Flye)
### Step 1: QC
```bash
# NanoPlot for long-read QC
NanoPlot --fastq reads.fastq.gz \
--outdir nanoplot_output \
--threads 8
```
### Step 2: Assembly with Flye
```bash
# ONT raw reads
flye --nano-raw reads.fastq.gz \
--out-dir flye_output \
--threads 16 \
--genome-size 5m
# ONT HQ reads (sup/dna_r10)
flye --nano-hq reads.fastq.gz \
--out-dir flye_output \
--threads 16 \
--genome-size 5m
# PacBio HiFi
flye --pacbio-hifi reads.fastq.gz \
--out-dir flye_output \
--threads 16 \
--genome-size 5m
```
### Step 3: Polishing with medaka
```bash
# Polish with medaka (for ONT)
medaka_consensus \
-i reads.fastq.gz \
-d flye_output/assembly.fasta \
-o medaka_output \
-t 16 \
-m r1041_e82_400bps_sup_v4.3.0 # Match your basecalling model
```
## Path C: Hybrid Assembly
```bash
# Flye with long reads, then polish with short reads
flye --nano-hq long_reads.fastq.gz \
--out-dir flye_output \
--threads 16 \
--genome-size 5m
# Polish with short reads using Pilon
bwa index flye_output/assembly.fasta
bwa mem -t 16 flye_output/assembly.fasta \
short_R1.fq.gz short_R2.fq.gz | \
samtools sort -@ 4 -o aligned.bam
samtools index aligned.bam
pilon --genome flye_output/assembly.fasta \
--frags aligned.bam \
--output hybrid_polished \
--threads 16
```
## Step 4: Quality Assessment
### QUAST
```bash
quast.py polished.fasta \
-r reference.fasta \
-g genes.gff \
-o quast_output \
-t 8
# Without reference
quast.py polished.fasta \
-o quast_output \
-t 8
```
### BUSCO
```bash
# Download lineage database
busco --download bacteria_odb10
# Run BUSCO
busco -i polished.fasta \
-l bacteria_odb10 \
-o busco_output \
-m genome \
-c 8
```
## Parameter Recommendations
| Tool | Parameter | Bacteria | Eukaryote |
|------|-----------|----------|-----------|
| SPAdes | --careful | Yes | Optional |
| SPAdes | -m | 64GB | 256GB+ |
| Flye | --genome-size | 5m | Species-specific |
| Flye | --meta | If metagenome | No |
| BUSCO | -l | bacteria_odb10 | eukaryota_odb10 |
## Troubleshooting
| Issue | Likely Cause | Solution |
|-------|--------------|----------|
| Fragmented assembly | Low coverage, repetitive genome | Increase coverage, use long reads |
| Low N50 | Short reads only | Add long reads for scaffolding |
| Low BUSCO | Incomplete assembly, wrong lineage | Check coverage, try different lineage |
| Assembly too large | Contamination, heterozygosity | Filter reads, check for contamination |
## Complete Pipeline Script
```bash
#!/bin/bash
set -e
THREADS=16
GENOME_SIZE="5m"
LONG_READS="long_reads.fastq.gz"
SHORT_R1="short_R1.fastq.gz"
SHORT_R2="short_R2.fastq.gz"
BUSCO_LINEAGE="bacteria_odb10"
OUTDIR="assembly_results"
mkdir -p ${OUTDIR}/{qc,assembly,polished,quast,busco}
# Step 1: QC
echo "=== QC ==="
NanoPlot --fastq ${LONG_READS} --outdir ${OUTDIR}/qc/nanoplot -t ${THREADS}
fastp -i ${SHORT_R1} -I ${SHORT_R2} \
-o ${OUTDIR}/qc/short_R1.fq.gz -O ${OUTDIR}/qc/short_R2.fq.gz \
--html ${OUTDIR}/qc/fastp.html
# Step 2: Assembly with Flye
echo "=== Assembly ==="
flye --nano-hq ${LONG_READS} \
--out-dir ${OUTDIR}/assembly \
--threads ${THREADS} \
--genome-size ${GENOME_SIZE}
# Step 3: Polish with short reads
echo "=== Polishing ==="
bwa index ${OUTDIR}/assembly/assembly.fasta
bwa mem -t ${THREADS} ${OUTDIR}/assembly/assembly.fasta \
${OUTDIR}/qc/short_R1.fq.gz ${OUTDIR}/qc/short_R2.fq.gz | \
samtools sort -@ 4 -o ${OUTDIR}/polished/aligned.bam
samtools index ${OUTDIR}/polished/aligned.bam
pilon --genome ${OUTDIR}/assembly/assembly.fasta \
--frags ${OUTDIR}/polished/aligned.bam \
--output ${OUTDIR}/polished/final \
--threads ${THREADS}
# Step 4: QC
echo "=== Quality Assessment ==="
quast.py ${OUTDIR}/polished/final.fasta -o ${OUTDIR}/quast -t ${THREADS}
busco -i ${OUTDIR}/polished/final.fasta -l ${BUSCO_LINEAGE} \
-o busco -m genome -c ${THREADS} --out_path ${OUTDIR}
echo "=== Assembly Complete ==="
echo "Final assembly: ${OUTDIR}/polished/final.fasta"
cat ${OUTDIR}/quast/report.txt
```
## Related Skills
- genome-assembly/short-read-assembly - SPAdes details
- genome-assembly/long-read-assembly - Flye, Canu, Hifiasm
- genome-assembly/assembly-polishing - Pilon, medaka, Racon
- genome-assembly/assembly-qc - QUAST, BUSCO metrics
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.