Dissecting Age-Specific Genetic Architecture of Vitiligo

Si's dataset contains results from integrative post-GWAS analyses dissecting the genetic differences between early-onset (EO) and late-onset (LO) vitiligo. The data includes genetic correlation estimates, functional annotation enrichment scores, and causal association results from methods like LDSC, SMR, and colocalization. Clinical validation results from qRT-PCR and ELISA on patient blood samples are also likely included.

Use Cases

• Estimating genetic correlation between EO and LO vitiligo subtypes based on LDSC regression results.
• Identifying cell-type-specific heritability enrichment across immune cell populations from stratified LDSC.
• Prioritizing core genetic targets for vitiligo subtypes using SMR and colocalization analysis results.
• Validating gene expression findings from genomic analyses with clinical qRT-PCR and ELISA data.

Strengths

• Integrates multiple advanced genomic analysis methods (LDSC, SMR, colocalization) for a comprehensive genetic investigation.
• Includes clinical validation data from patient blood samples, bridging genomic findings with experimental biology.
• Released under a permissive CC-BY-4.0 license, facilitating reuse and redistribution.

Limitations

• Column names and a precise row count are not provided, limiting understanding of the data's granular structure.
• The dataset's primary format is XLSX, which may be less efficient for large-scale computational analysis than plain-text formats.
• The author's full name and institutional affiliation are not specified, reducing provenance clarity.

Provenance

Source

Author listed as 'Si'. Organization is unknown.

Collection Method

Generated through integrative post-GWAS analysis including LDSC, SMR, colocalization, and clinical validation via qRT-PCR/ELISA.

Time Range

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Freshness

Last updated on 2026-03-22.

Geography

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