domains / science / structural-variant-calling / structural-variant-calling

structural-variant-calling

Skill card

combined

The two skills cover the same task but with different depth and scope. The first copy (OpenClaw) is a practical, command-line recipe book for short-read SV calling (Manta, Delly, LUMPY) with specific bash commands for configuration, execution, merging, and filtering. The second copy (GPTomics) is a conceptual and strategic guide that explains the underlying signals (RP, SR, RD, Assembly), maps callers to their signal strengths/blind spots, includes long-read callers (Sniffles2, cuteSV, pbsv), and discusses version compatibility and benchmarking (Truvari). The first copy lacks the theoretical framework and long-read details; the second copy lacks the specific, copy-pasteable command workflows for the short-read tools it mentions. Combining them provides both the 'how' (commands) and the 'why/when' (signal logic and caller selection).

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Other copies

Combined skill

# Structural Variant Calling

## 1. Caller Selection & Signal Logic
Structural variants (SVs) are inferred from four orthogonal signals: Discordant Pairs (RP), Split Reads (SR), Read Depth (RD), and Local Assembly (AS). Choose callers based on the signals they fuse and your data type.

**Short-Read Callers:**
- **Manta**: Fuses RP, SR, and targeted Assembly. Best for default germline/somatic calling. Fast and accurate.
- **Delly**: Fuses RP, SR, and RD (via `delly cnv`). Good for joint calling and somatic filtering.
- **LUMPY/smoove**: Fuses RP and SR. No assembly or RD. Good for large SVs but misses small insertions.
- **GRIDSS2/SvABA**: Use genome-wide assembly. Higher precision for complex events.

**Long-Read Callers (ONT/PacBio):**
- **Sniffles2**: Population-scale, multisample.
- **cuteSV**: Fast, accurate for all SV types.
- **pbsv**: Official PacBio caller.

## 2. Short-Read Workflow (Manta Example)

### Configure and Run Manta
```bash
# Germline
configManta.py \
    --bam sample.bam \
    --referenceFasta reference.fa \
    --runDir manta_run

manta_run/runWorkflow.py -j 8

# Somatic
configManta.py \
    --tumorBam tumor.bam \
    --normalBam normal.bam \
    --referenceFasta reference.fa \
    --runDir manta_somatic

manta_somatic/runWorkflow.py -j 8
```

### Run Delly
```bash
delly call -g reference.fa -o sv_calls.bcf sample.bam
bcftools view sv_calls.bcf > sv_calls.vcf
```

### Run LUMPY (via smoove)
```bash
smoove call \
    --name sample \
    --fasta reference.fa \
    --outdir smoove_output \
    -p 8 \
    sample.bam
```

## 3. Merging and Filtering

### Merge Callers
Use SURVIVOR for position-based merging or Truvari for sequence-aware merging (preferred for benchmarking/complex SVs).

```bash
# SURVIVOR Example
SURVIVOR merge vcf_list.txt 1000 2 1 1 0 50 merged_svs.vcf
```

### Filter
```bash
# Quality and Size
bcftools view -i 'QUAL >= 20 && ABS(SVLEN) >= 50' svs.vcf > svs.filtered.vcf

# Type-specific
bcftools view -i 'SVTYPE="DEL"' svs.vcf > deletions.vcf
```

## 4. Annotation
Use AnnotSV to annotate genes, DGV, gnomAD-SV, and ClinVar.

```bash
AnnotSV \
    -SVinputFile svs.vcf \
    -genomeBuild GRCh38 \
    -outputFile annotated_svs
```

## 5. Version Compatibility
Verify tool versions before running. Note that flags may change between major versions (e.g., Truvari 4.x uses `--pctseq` instead of `--pctsim`). Always check `--help` for the installed version.