--> --- name: bio-variant-annotation description: Comprehensive variant annotation using bcftools annotate/csq, VEP, SnpEff, and ANNOVAR. Add database annotations, predict functional consequences, and assess clinical significance. Use when annotating variants with functional and clinical information. tool_type: mixed primary_tool: VEP measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---
Scanned 9/4/2026
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---
name: bio-variant-annotation
description: Comprehensive variant annotation using bcftools annotate/csq, VEP, SnpEff, and ANNOVAR. Add database annotations, predict functional consequences, and assess clinical significance. Use when annotating variants with functional and clinical information.
tool_type: mixed
primary_tool: VEP
measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.
allowed-tools:
- read_file
- run_shell_command
---
# Variant Annotation
## Tool Comparison
| Tool | Best For | Speed | Output |
|------|----------|-------|--------|
| bcftools csq | Simple consequence prediction | Fast | VCF |
| VEP | Comprehensive with plugins | Moderate | VCF/TXT |
| SnpEff | Fast batch annotation | Fast | VCF |
| ANNOVAR | Flexible databases | Moderate | TXT |
## bcftools annotate
### Add Annotations from Database
```bash
bcftools annotate -a dbsnp.vcf.gz -c ID input.vcf.gz -Oz -o annotated.vcf.gz
```
### Annotation Columns (`-c`)
| Option | Description |
|--------|-------------|
| `ID` | Copy ID column |
| `INFO` | Copy all INFO fields |
| `INFO/TAG` | Copy specific INFO field |
| `+INFO/TAG` | Add to existing values |
### Add rsIDs from dbSNP
```bash
bcftools annotate -a dbsnp.vcf.gz -c ID input.vcf.gz -Oz -o with_rsids.vcf.gz
```
### Add Multiple Annotations
```bash
bcftools annotate -a database.vcf.gz -c ID,INFO/AF,INFO/CAF input.vcf.gz -Oz -o annotated.vcf.gz
```
### Add from BED/TAB Files
```bash
# BED with 4th column as annotation
bcftools annotate -a regions.bed.gz -c CHROM,FROM,TO,INFO/REGION \
-h <(echo '##INFO=<ID=REGION,Number=1,Type=String,Description="Region name">') \
input.vcf.gz -Oz -o annotated.vcf.gz
# Tab file: CHROM POS VALUE
bcftools annotate -a annotations.tab.gz -c CHROM,POS,INFO/SCORE \
-h <(echo '##INFO=<ID=SCORE,Number=1,Type=Float,Description="Custom score">') \
input.vcf.gz -Oz -o annotated.vcf.gz
```
### Remove Annotations
```bash
bcftools annotate -x INFO/DP,INFO/MQ input.vcf.gz -Oz -o clean.vcf.gz
bcftools annotate -x INFO input.vcf.gz -Oz -o minimal.vcf.gz # Remove all INFO
```
### Set ID from Fields
```bash
bcftools annotate --set-id '%CHROM\_%POS\_%REF\_%ALT' input.vcf.gz -Oz -o with_ids.vcf.gz
```
## bcftools csq
Simple consequence prediction using GFF annotation.
```bash
bcftools csq -f reference.fa -g genes.gff3.gz input.vcf.gz -Oz -o consequences.vcf.gz
```
### Consequence Types
| Consequence | Description |
|-------------|-------------|
| `synonymous` | No amino acid change |
| `missense` | Amino acid change |
| `stop_gained` | Introduces stop codon |
| `frameshift` | Changes reading frame |
| `splice_donor/acceptor` | Affects splicing |
## Ensembl VEP
### Installation
```bash
conda install -c bioconda ensembl-vep
vep_install -a cf -s homo_sapiens -y GRCh38 --CONVERT
```
### Basic Annotation
```bash
vep -i input.vcf -o output.vcf --vcf --cache --offline
```
### Comprehensive Annotation
```bash
vep -i input.vcf -o output.vcf \
--vcf \
--cache --offline \
--species homo_sapiens \
--assembly GRCh38 \
--everything \
--fork 4
```
### --everything Enables
- `--sift b` - SIFT predictions
- `--polyphen b` - PolyPhen predictions
- `--hgvs` - HGVS nomenclature
- `--symbol` - Gene symbols
- `--canonical` - Canonical transcript
- `--af` - 1000 Genomes frequencies
- `--af_gnomade/g` - gnomAD frequencies
- `--pubmed` - PubMed IDs
### Filter by Impact
```bash
vep -i input.vcf -o output.vcf --vcf \
--cache --offline \
--pick \
--filter "IMPACT in HIGH,MODERATE"
```
### Plugins
```bash
# CADD scores
vep -i input.vcf -o output.vcf --vcf \
--cache --offline \
--plugin CADD,whole_genome_SNVs.tsv.gz
# dbNSFP (multiple predictors)
vep -i input.vcf -o output.vcf --vcf \
--cache --offline \
--plugin dbNSFP,dbNSFP4.3a.gz,ALL
# Multiple plugins
vep -i input.vcf -o output.vcf --vcf \
--cache --offline \
--plugin CADD,cadd.tsv.gz \
--plugin dbNSFP,dbnsfp.gz,SIFT_score,Polyphen2_HDIV_score \
--plugin SpliceAI,spliceai.vcf.gz
```
### VEP Output Fields
| Field | Description |
|-------|-------------|
| Consequence | SO term (e.g., missense_variant) |
| IMPACT | HIGH, MODERATE, LOW, MODIFIER |
| SYMBOL | Gene symbol |
| HGVSc/HGVSp | HGVS coding/protein change |
| SIFT/PolyPhen | Pathogenicity predictions |
## SnpEff
### Installation
```bash
conda install -c bioconda snpeff
snpEff download GRCh38.105
```
### Basic Annotation
```bash
snpEff ann GRCh38.105 input.vcf > output.vcf
```
### With Statistics
```bash
snpEff ann -v -stats stats.html -csvStats stats.csv GRCh38.105 input.vcf > output.vcf
```
### Filter by Impact
```bash
snpEff ann GRCh38.105 input.vcf | \
SnpSift filter "(ANN[*].IMPACT = 'HIGH')" > high_impact.vcf
```
### SnpEff Impact Categories
| Impact | Examples |
|--------|----------|
| HIGH | Stop gained, frameshift, splice donor/acceptor |
| MODERATE | Missense, inframe indel |
| LOW | Synonymous, splice region |
| MODIFIER | Intron, intergenic, UTR |
### SnpSift Database Annotations
```bash
# dbSNP
SnpSift annotate dbsnp.vcf.gz input.vcf > annotated.vcf
# ClinVar
SnpSift annotate clinvar.vcf.gz input.vcf > annotated.vcf
# dbNSFP
SnpSift dbnsfp -db dbNSFP4.3a.txt.gz input.vcf > annotated.vcf
# Chain multiple
snpEff ann GRCh38.105 input.vcf | \
SnpSift annotate dbsnp.vcf.gz | \
SnpSift annotate clinvar.vcf.gz > fully_annotated.vcf
```
### SnpSift Filtering
```bash
SnpSift filter "(QUAL >= 30) & (DP >= 10)" input.vcf > filtered.vcf
SnpSift filter "(exists CLNSIG) & (CLNSIG has 'Pathogenic')" input.vcf > pathogenic.vcf
```
## ANNOVAR
### Installation
```bash
# Download from https://annovar.openbioinformatics.org/ (registration required)
annotate_variation.pl -buildver hg38 -downdb -webfrom annovar refGene humandb/
annotate_variation.pl -buildver hg38 -downdb -webfrom annovar gnomad30_genome humandb/
```
### Table Annotation
```bash
table_annovar.pl input.vcf humandb/ \
-buildver hg38 \
-out annotated \
-remove \
-protocol refGene,gnomad30_genome,clinvar_20230416,dbnsfp42a \
-operation g,f,f,f \
-nastring . \
-vcfinput
```
## Python: Parse Annotated VCF
### Parse VEP CSQ
```python
from cyvcf2 import VCF
def parse_vep_csq(csq_string, csq_header):
fields = csq_header.split('|')
values = csq_string.split('|')
return dict(zip(fields, values))
vcf = VCF('vep_output.vcf')
csq_header = None
for h in vcf.header_iter():
if h['HeaderType'] == 'INFO' and h['ID'] == 'CSQ':
csq_header = h['Description'].split('Format: ')[1].rstrip('"')
break
for variant in vcf:
csq = variant.INFO.get('CSQ')
if csq:
for transcript in csq.split(','):
parsed = parse_vep_csq(transcript, csq_header)
if parsed.get('IMPACT') in ('HIGH', 'MODERATE'):
print(f"{variant.CHROM}:{variant.POS} {parsed['SYMBOL']} {parsed['Consequence']}")
```
### Parse SnpEff ANN
```python
from cyvcf2 import VCF
def parse_snpeff_ann(ann_string):
fields = ['Allele', 'Annotation', 'Impact', 'Gene_Name', 'Gene_ID',
'Feature_Type', 'Feature_ID', 'Transcript_BioType', 'Rank',
'HGVS_c', 'HGVS_p', 'cDNA_pos', 'CDS_pos', 'Protein_pos', 'Distance']
values = ann_string.split('|')
return dict(zip(fields, values[:len(fields)]))
for variant in VCF('snpeff_output.vcf'):
ann = variant.INFO.get('ANN')
if ann:
for transcript in ann.split(','):
parsed = parse_snpeff_ann(transcript)
if parsed['Impact'] == 'HIGH':
print(f"{variant.CHROM}:{variant.POS} {parsed['Gene_Name']} {parsed['Annotation']}")
```
## Complete Annotation Pipeline
```bash
#!/bin/bash
set -euo pipefail
INPUT=$1
REFERENCE=$2
VEP_CACHE=$3
OUTPUT_PREFIX=$4
# Normalize variants
bcftools norm -f $REFERENCE -m-any $INPUT -Oz -o ${OUTPUT_PREFIX}_norm.vcf.gz
bcftools index ${OUTPUT_PREFIX}_norm.vcf.gz
# VEP annotation
vep -i ${OUTPUT_PREFIX}_norm.vcf.gz \
-o ${OUTPUT_PREFIX}_vep.vcf \
--vcf --cache --offline --dir_cache $VEP_CACHE \
--assembly GRCh38 --everything --pick --fork 4
bgzip ${OUTPUT_PREFIX}_vep.vcf
bcftools index ${OUTPUT_PREFIX}_vep.vcf.gz
# Filter high/moderate impact
bcftools view -i 'INFO/CSQ~"HIGH" || INFO/CSQ~"MODERATE"' \
${OUTPUT_PREFIX}_vep.vcf.gz -Oz -o ${OUTPUT_PREFIX}_filtered.vcf.gz
```
## Pathogenicity Predictors
| Predictor | Deleterious | Benign |
|-----------|-------------|--------|
| SIFT | < 0.05 | >= 0.05 |
| PolyPhen-2 (HDIV) | > 0.957 (probably), > 0.453 (possibly) | <= 0.453 |
| CADD | > 20 (top 1%), > 30 (top 0.1%) | < 10 |
| REVEL | > 0.5 | < 0.5 |
## Clinical Significance (ClinVar)
| Code | Meaning |
|------|---------|
| Pathogenic | Disease-causing |
| Likely_pathogenic | Probably disease-causing |
| Uncertain_significance | VUS |
| Likely_benign | Probably not disease-causing |
| Benign | Not disease-causing |
## Quick Reference
| Task | Command |
|------|---------|
| Add rsIDs | `bcftools annotate -a dbsnp.vcf.gz -c ID in.vcf.gz` |
| VEP annotation | `vep -i in.vcf -o out.vcf --vcf --cache --everything` |
| SnpEff annotation | `snpEff ann GRCh38.105 in.vcf > out.vcf` |
| Consequences only | `bcftools csq -f ref.fa -g genes.gff in.vcf.gz` |
## Related Skills
- variant-calling/variant-normalization - Normalize before annotating
- variant-calling/filtering-best-practices - Filter by annotations
- variant-calling/vcf-basics - Query annotated fields
- database-access/entrez-fetch - Download annotation databases
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