Our Science – Vgenomics – Solutions for Rare Diseases

We harness cutting‐edge AI and multi‐omics integration to turn complex biological data into clear, actionable insights. This accelerates rare‐disease diagnosis, unlocking new therapeutic targets in one seamless platform.

Enabling access to AI-powered analysis, variant interpretation, and VUS handling through RgenX-DM

Data Ingestion

Accept raw FASTQ and VCF files from any sequencing platform (Illumina, PacBio, or Nanopore) in a single, streamlined process.

Variant Annotation

Enrich each variant with data from more than 40 databases, such as ClinVar, gnomAD, and custom databases, plus 15+ in silico predicted tools like PolyPhen, SIFT, and Mutation Taster.

Explainable Variant Prioritization

Apply machine‐learning models that combine ACMG guidelines, in silico scores (CADD, REVEL), and phenotype matches to rank variants, complete with clear feature breakdowns and phenotype‐genotype matching.

Reporting & Collaboration

Generate automated draft reports formatted to ACMG standards, including variant tables, evidence summaries, and treatment recommendations ready for EMR export.

The validation of our workflow, conducted on 200 clinical samples, demonstrated a sensitivity greater than 99.4%.

Gain access to expertly curated information from over 50 leading databases, including ClinVar, Orphanet, HPO Ontology, HGMD, gnomAD, dbSNP, UniProt, OMIM, COSMIC, and more, integrated into proprietary knowledge graphs that capture essential biomedical relationships.

160,822

disease-gene associations

80,126

drug-disease links

129,568

drug-phenotype connections

303,020

disease-phenotype mappings

7,898

exposure-disease/biological process associations

900,000

VUS-gene associations

300,000

phenotype-disease connections

17,000

variant-gene relationships

Case Studies

Keratoconus Biomarker
Discovery

Congenital Nephrotic
Syndrome Diagnosis – Proband

Joubert Syndrome 17
Diagnosis – Trios

Our Publications

KMT2C Polymorphism in Familial Hypospadias

Familial Hypospadias: CNVs in a Quad Family

PFV3D: Protein Feature Visualisation on 3D structure

Machine-Learning Prediction of COVID-19 Prognostic Biomarkers from Clinical and Proteomics Data

Integrative analyses of SARS-CoV-2 genomes across locations reveal features for host-virus interaction, pathogenesis, and novel therapy clues

Transcriptional signals of T-cell and corticosteroid-sensitive genes associate with future acute cellular rejection in cardiac allografts

Dataset of mutational analysis, miRNAs targeting SARS-CoV-2 genes and host gene expression in SARS-CoV and SARS-CoV-2 infections

Host miRNA/TF Co-regulatory Networks Identify Novel SARS-CoV-2 Drug Targets

Meta-analysis & Validation of Nasopharyngeal Omics Identify COVID-19 Prognostic Markers and Targets

Novel Meta-analysis of heterogeneous high-throughput gene expression data reveals dysregulated interactions and pathways in asthma

Role of CYP1B1, p.E229K and p.R368H in 120 families with sporadic juvenile onset open-angle glaucoma

Comparative SAR-CoV2 and coronavirus genomes across locations reveal features for host-virus interaction and pathogenesis

At Vgenomics, we believe the future of precision medicine lies in tightly integrating clinical AI, multi‐omics analytics, and collaborative discovery. By breaking down silos between symptom triage, molecular diagnosis, and therapeutic development, we’re accelerating the path from “bench to bedside” and ensuring that every patient benefits from the latest scientific advances.