CandiHap

CandiHap identifies candidate causal single nucleotide polymorphisms (SNPs) and genes from GWAS results by integrating linkage disequilibrium, SNP annotation, haplotype analysis, and haplotype trait statistics on VCF-formatted variant data.

Key Features:

• Input format: Uses VCF (Variant Call Format) files as the primary input for variant data.
• Candidate preselection: Preselects candidate causal SNPs and genes from GWAS datasets.
• Linkage disequilibrium integration: Integrates linkage disequilibrium (LD) results to relate SNPs and genomic regions.
• SNP annotation: Performs SNP annotation to provide functional and positional information for variants.
• Haplotype analysis: Conducts haplotype analysis and computes haplotype-level trait statistics.
• Targeted region analysis: Allows specification of particular genes or linkage regions based on GWAS findings for focused analysis.
• LD vs causal discrimination: Distinguishes SNPs in linkage disequilibrium from likely causal variants through combined analyses.
• Cross-species applicability: Applicable to any species, including plants, animals, and bacteria.
• Result formats: Produces tabular outputs and vector-graph visualizations of analysis results.

Scientific Applications:

• GWAS interpretation: Prioritizing candidate causal variants and genes from GWAS results.
• Haplotype–trait analysis: Assessing associations between haplotypes and phenotypic traits using haplotype-level statistics.
• Causal inference: Distinguishing LD proxies from likely causal variants to support functional follow-up studies.
• Comparative genetics: Applying candidate causal variant and gene identification across plants, animals, and bacterial genetics.

Methodology:

Operates on VCF files, integrates linkage disequilibrium results, applies SNP annotation, performs haplotype analysis and haplotype trait-statistics, and supports targeted analysis of specified genes or linkage regions.