Genomic Consultant

A practical genomics analysis toolkit for Trio WES (Whole Exome Sequencing) data analysis, including ClinVar/ACMG annotation, GWAS trait analysis, and pharmacogenomics.

Analysis Scripts

1. Trio Analysis (trio_analysis.py)

Comprehensive trio-based variant analysis with de novo detection, compound heterozygosity, and inheritance pattern annotation.

python trio_analysis.py <vcf_path> <output_dir>

2. ClinVar/ACMG Annotation (clinvar_acmg_annotate.py)

Annotates variants with ClinVar clinical significance and generates ACMG-style evidence tags.

python clinvar_acmg_annotate.py <vcf_path> <output_path> [sample_idx]

3. GWAS Comprehensive Analysis (gwas_comprehensive.py)

Comprehensive GWAS trait analysis with 201 curated SNPs across 18 categories:

• Gout / Uric acid metabolism
• Kidney disease
• Hearing loss
• Autoimmune diseases
• Cancer risk
• Blood clotting / Thrombosis
• Thyroid disorders
• Bone health / Osteoporosis
• Liver disease (NAFLD)
• Migraine
• Longevity / Aging
• Sleep
• Skin conditions
• Cardiovascular disease
• Metabolic disorders
• Eye conditions
• Neuropsychiatric
• Other traits

python gwas_comprehensive.py <vcf_path> <output_path> [sample_idx]

4. PharmGKB Full Analysis (pharmgkb_full_analysis.py)

Comprehensive pharmacogenomics analysis using the PharmGKB clinical annotations database.

python pharmgkb_full_analysis.py <vcf_path> <output_path> [sample_idx]

5. GWAS Trait Lookup (gwas_trait_lookup.py)

Original curated GWAS trait lookup (smaller SNP set).

python gwas_trait_lookup.py <vcf_path> <output_path> [sample_idx]

6. Basic Pharmacogenomics (pharmacogenomics.py)

Basic pharmacogenomics analysis with common drug-gene interactions.

Prerequisites

• Python 3.8+
• conda environment with bioinformatics tools:

  conda create -n genomics python=3.10
  conda activate genomics
  conda install -c bioconda bcftools snpeff gatk4
  

Reference Databases Required

• ClinVar: VCF from NCBI
• PharmGKB: Clinical annotations TSV
• dbSNP: For rsID annotation
• GRCh37/hg19 reference genome

Data Directory Structure

/Volumes/NV2/
├── genomics_analysis/
│   └── vcf/
│       ├── trio_joint.vcf.gz          # Joint-called VCF
│       ├── trio_joint.rsid.vcf.gz     # With rsID annotations
│       └── trio_joint.snpeff.vcf      # With SnpEff annotations
└── genomics_reference/
    ├── clinvar/
    ├── pharmgkb/
    ├── dbsnp/
    └── gwas_catalog/

Sample Index Mapping

For trio VCF files:

• Index 0: Mother
• Index 1: Father
• Index 2: Proband

Output Reports

Each script generates detailed reports including:

• Summary statistics
• Risk variant identification
• Family comparison (for trio data)
• Clinical annotations and recommendations

License

Private use only.