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bio-variant-normalization

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Normalize indel representation, decompose MNPs, and split multiallelic variants using bcftools norm. Use when comparing variants from different callers, preparing VCF for database annotation, or merging VCFs from multiple sources.

General

What this skill does


## Version Compatibility

Reference examples tested with: bcftools 1.19+, cyvcf2 0.30+

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

The `--atomize` flag requires bcftools 1.17+. Earlier versions require `vt decompose_blocksub` as an alternative.

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

# Variant Normalization

Left-align indels, decompose MNPs, and split multiallelic sites using bcftools norm.

## When Normalization is Mandatory

Not normalizing before certain operations leads to missed matches and false discordance. Normalization is required:

- **Before comparing variants from different callers.** Each caller may represent the same indel at different positions or encode MNPs differently. Without normalization, identical variants appear discordant.
- **Before database annotation.** dbSNP, ClinVar, and gnomAD store variants in canonical left-aligned, parsimonious representation. A right-aligned or non-parsimonious indel will fail to match its database entry.
- **Before merging VCF files from different sources.** `bcftools merge` matches on CHROM/POS/REF/ALT; different representations of the same variant produce duplicate entries instead of a single merged record.
- **Before any variant set operations.** Intersection (`bcftools isec`), complement, and union operations all rely on exact positional matching. Non-normalized variants silently fall through set comparisons.

Normalization is generally safe to skip only when a single caller produced all variants and no cross-file comparison or database lookup is needed.

## Why Normalize?

The same variant can be represented multiple ways:

```
chr1  100  ATCG  A      (right-aligned)
chr1  100  ATC   A      (left-aligned, parsimonious -- the canonical form)
chr1  101  TCG   T      (shifted position, different anchor base)
```

The VCF specification mandates left-aligned, parsimonious representation, but not all callers comply. Normalization enforces this canonical form.

## Recommended Normalization Pipeline

The order of operations matters. Performing these steps out of order can produce incorrect results (e.g., left-aligning a multiallelic record may normalize differently than splitting first, then left-aligning each biallelic record independently).

The correct order:

1. **Decompose MNPs** into atomic SNPs (`--atomize`)
2. **Split multiallelic** sites into biallelic records (`-m-`)
3. **Left-align and trim** against the reference (`-f reference.fa`)

Combined as a piped pipeline:

```bash
bcftools norm --atomize input.vcf.gz | \
    bcftools norm -m- | \
    bcftools norm -f reference.fa -Oz -o normalized.vcf.gz
bcftools index normalized.vcf.gz
```

For VCFs without MNPs (e.g., GATK HaplotypeCaller output, which does not emit MNPs), the atomize step can be skipped:

```bash
bcftools norm -m- input.vcf.gz | \
    bcftools norm -f reference.fa -Oz -o normalized.vcf.gz
```

A single-pass `bcftools norm -f ref.fa -m-any` is acceptable for basic use cases but does not control the decomposition order and skips MNP atomization.

## Left-Alignment

**"Normalize my VCF before comparing callers"** -> Left-align indel representations and split multiallelic sites for consistent variant comparison.

```bash
bcftools norm -f reference.fa input.vcf.gz -Oz -o normalized.vcf.gz
```

Requires reference FASTA to determine the leftmost position. The reference must be the same genome build used during variant calling; mismatches between builds silently produce wrong results even when REF alleles happen to match locally.

### Check for Normalization Issues

```bash
bcftools norm -f reference.fa -c s input.vcf.gz > /dev/null
```

Check modes (`-c`):
- `w` - Warn on mismatch (default)
- `e` - Error on mismatch
- `x` - Exclude mismatches
- `s` - Set correct REF from reference

## Multiallelic Splitting

### Split Multiallelic to Biallelic

```bash
bcftools norm -m-any input.vcf.gz -Oz -o split.vcf.gz
```

Before:
```
chr1  100  .  A  G,T  30  PASS  .  GT  1/2
```

After:
```
chr1  100  .  A  G  30  PASS  .  GT  1/0
chr1  100  .  A  T  30  PASS  .  GT  0/1
```

### Splitting Caveats

Splitting creates artificial missing information. A sample with genotype 1/2 (compound heterozygous for two different ALT alleles) becomes 0/1 in both split records. The information that both alleles were present at the same site in the same individual is lost. This has consequences for:

- **Phasing and compound heterozygosity detection.** Clinical pipelines that identify compound hets (two damaging variants on different alleles of the same gene) can misinterpret split records as independent heterozygous calls rather than co-occurring alleles at one site.
- **Allele depth (AD) interpretation.** AD values are retained per allele in each split record, but the genotype relationship between alleles at the same site is gone.
- **Population allele frequency estimation.** Splitting followed by naive frequency calculation can double-count samples at multiallelic sites.

Decision guidance:

| Downstream tool | Splitting required? | Rationale |
|----------------|-------------------|-----------|
| PLINK, PLINK2 | Yes | PLINK requires biallelic records |
| Most GWAS tools | Yes | Expect biallelic sites |
| Hail | No | Handles multiallelics natively; splitting loses information |
| bcftools csq | No | Supports multiallelic consequence calling |
| VEP | Either | Handles both; multiallelic may give richer output |
| ClinVar matching | Yes | ClinVar entries are biallelic |

When a downstream tool does not require splitting, prefer keeping multiallelic sites intact to preserve genotype relationships.

### Split Options

| Option | Description |
|--------|-------------|
| `-m-any` | Split all multiallelic sites |
| `-m-snps` | Split multiallelic SNPs only |
| `-m-indels` | Split multiallelic indels only |
| `-m-both` | Split SNPs and indels separately |
| `-m+any` | Join biallelic sites into multiallelic |
| `-m+snps` | Join biallelic SNPs |
| `-m+indels` | Join biallelic indels |
| `-m+both` | Join SNPs and indels separately |

### Join Biallelic to Multiallelic

```bash
bcftools norm -m+any input.vcf.gz -Oz -o merged.vcf.gz
```

Rejoining after analysis can restore compound heterozygosity context, but only if the split records were not independently filtered (removing one allele of a 1/2 site makes the remaining record misleading).

## Atomize Complex Variants (MNP Decomposition)

Multi-nucleotide polymorphisms (MNPs) are adjacent substitutions reported as a single record (e.g., ATG->GCA). Not all callers emit MNPs:

| Caller | Emits MNPs? | Notes |
|--------|------------|-------|
| FreeBayes | Yes | Reports MNPs and complex events natively |
| Octopus | Yes | Local haplotype-aware, emits block substitutions |
| GATK HaplotypeCaller | No | Decomposes variants during calling; may emit nearby SNPs in the same haplotype block |
| DeepVariant | Rarely | Primarily emits SNPs and indels |

Decomposing MNPs is necessary when comparing output from callers that represent them differently. Without atomization, an MNP from FreeBayes will not match the equivalent individual SNPs from GATK.

### Atomize MNPs to SNPs

```bash
bcftools norm --atomize input.vcf.gz -Oz -o atomized.vcf.gz
```

Before:
```
chr1  100  .  ATG  GCA  30  PASS
```

After:
```
chr1  100  .  A  G  30  PASS
chr1  101  .  T  C  30  PASS
chr1  102  .  G  A  30  PASS
```

**Caveat:** Decomposition loses local phasing information. The original MNP record guarantees that A->G, T->C, and G->A occur on the same haplotype. After atomization, this co-occurrence is no longer explicit. If downstream analysis requires haplotype-aware interpretation (e.g., amino acid change prediction where the codon change matters), atom

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