LOCUS ™
Linking Omics for Causal Understanding of disease Signatures
Context
Systematic characterisation of disease-associated loci with LOCUS™
We enable researchers to translate genomic signals into causal disease mechanisms by prioritising effector genes, predicting biomarkers, and identifying actionable therapeutic targets.
Bring your own GWAS data or start with a published study, and run the full post-GWAS suite – meta-analysis, variant annotation, fine-mapping, Mendelian randomisation, colocalization, TWAS, PRS, PheWAS, genetic correlation, and functional enrichment – to decode causal disease insights.
LOCUS™ Agent auto-generates the right workflow for your disease and use case, interprets each pipeline’s output, and triangulates results into an effector gene/target prioritisation scorecard – giving you the precise biological context to uncover disease pathophysiology, validate outcomes, and accelerate discovery.
Use Cases
An Integrated Evidence Framework
Each use case draws on the same underlying pipelines and triangulation framework, configured differently depending on the question.
Prioritization
Target Prioritization
Score and rank a pre-defined candidate list against multi-pipeline genomic evidence for a disease of interest.Discovery
Target Identification
Genome-wide, proteome-wide scan to identify and rank novel candidate targets directly from GWAS summary statistics.Correlation
Indication Expansion
Genetic correlation and PheWAS evidence surface phenotypes sharing mechanism with the disease of interest.Mechanism
Disease Mechanism
MAGMA tissue enrichment, G2F pathway mapping, TWAS and fine-mapped annotation build a mechanistic picture of tissue and pathway involvement.Repurposing
Drug Repurposing
Tier 1/2 targets are cross-referenced against existing compounds acting on the same gene or pathway via DBTIPS.Biomarkers
Biomarker Discovery
Proteins with robust MR and colocalisation support are flagged as candidate circulating biomarkers, contextualised by PheWAS specificity.Why LOCUS™
GWAS studies offer unmatched depth into disease causality — but that depth brings complexity that can slow discovery down. LOCUS™ helps you cut through it with an AI-powered framework that integrates, analyses, and interprets multi-omics data into a holistic view of disease mechanisms, causal genes, and biological variability — adapting to whether you’re hunting for new drug targets or translational insight.
Features
Where LOCUS™ fits in your research
Discover our offerings across the biopharma value chain
Ready to turn your omics data into biological insight?
Talk to our team to set up access or see a live demonstration with your disease of interest.