LD-annot

LD-annot annotates candidate single nucleotide polymorphisms (SNPs) and their linked genes by delineating linkage disequilibrium (LD) regions to support interpretation of genotype–phenotype associations.

Key Features:

• Automated Annotation Pipeline: Automates delineation of LD regions around candidate SNPs and annotates all genes within those regions, supporting GWAS follow-up.
• Experiment-Specific LD Estimation: Estimates experiment-specific linkage disequilibrium to define genomic regions linked to each genetic marker.
• Flexible Data Compatibility: Processes genotypic data from SNP arrays, genotyping-by-sequencing (GBS), and VCF-format datasets.
• Efficient Computational Design: Implements a checkpoint procedure that enables testing multiple LD thresholds without rerunning the full analysis.
• Broad Applicability: Has been applied to breeding populations, within-pedigree SNP datasets from whole genome sequencing (WGS), and extensive multi-variety SNP datasets from WGS.

Scientific Applications:

• Candidate SNP and gene annotation: Annotating candidate SNPs and their linked genes to prioritize targets for downstream functional study.
• GWAS follow-up: Supporting interpretation of genome-wide association study (GWAS) signals by mapping associated markers to LD-defined gene sets.
• Genetic architecture analysis: Investigating the genetic architecture of complex traits and aiding discovery of causal polymorphisms.
• Breeding and diversity studies: Informing analyses of breeding populations and comparative analysis of multi-variety WGS SNP datasets.

Methodology:

Delineates regions of interest based on linkage disequilibrium surrounding candidate SNPs; estimates experiment-specific LD; extracts gene identifiers, genomic coordinates, and annotations for genes in LD with candidate polymorphisms; accepts genotypic input in VCF format; and uses a checkpoint procedure to test multiple linkage thresholds, implemented with standard bioinformatics tools and languages.