Locusbased

Locusbased is a term used in genetics and computational genomics to describe approaches, analyses, or data representations that focus on individual genetic loci—specific positions in the genome—rather than evaluating patterns across the entire genome. The concept centers on locus-level inference, often defined by fixed genomic coordinates or functional boundaries, and is employed in tasks such as fine-mapping, regional association studies, and locus-specific heritability estimation.

In practice, locusbased methods test or estimate associations within predefined loci or LD blocks, integrating information about linkage disequilibrium, recombination, and functional annotations to prioritize potentially causal variants. This local focus can complement genome-wide strategies by providing higher-resolution localization within regions already implicated by broader scans.

Compared with genome-wide approaches like GWAS, locusbased analyses aim for precise localization of signals within targeted regions, facilitating biological interpretation and downstream experimental validation. They are commonly used in post-GWAS workflows to dissect regional signals, assess the contribution of a single locus to trait variance, and refine candidate variants for functional studies.

Limitations of locusbased methods include potential under-detection of distributed, polygenic effects that span multiple loci and the dependence on how loci are defined, which can influence results. Methodological variations exist in how loci are delineated, how LD is modeled, and how functional data are integrated.

See also: fine-mapping, regional association study, LD blocks, gene-based tests, functional annotation.