Emedgene

Emedgene software is designed to unlock genomic insights for hereditary diseases by streamlining tertiary analysis workflows in rare disease genomics and other germline research applications. It accelerates the time and certainty in user-defined variant interpretation, prioritization, curation, and research report generation from sequencing and microarrays.

With explainable AI (XAI) and automation, Emedgene enhances efficiency in workflows supporting genomes, exomes, virtual panels, targeted panels, and microarrays. This allows users to save valuable time per subject and per project, from dozens of samples to population-scale studies.

Integration and Growth

The software unifies wet lab and dry lab processes, simplifying and securing complete sequencing or microarray workflows. It integrates with DRAGEN secondary analysis for accurate, comprehensive, and efficient variant calling, speeding user-driven variant interpretation by up to 75% per subject.

Emedgene is powered for growth, keeping pace with evolving science, technology, and test volumes through up-to-date knowledge sources, automated curation capabilities, and expert support.

Key Features

• Explainable AI (XAI): Provides high accuracy insights backed by evidence, increasing workflow efficiency and confidence.
• Automation: Optimizes workflows for standard operating procedures across test types, maximizing efficiency and scale.
• Powerful API Interoperability: Links tertiary analysis with laboratory information management systems, storage, pipelines, and more.

Emedgene supports a wide range of applications, including whole-genome sequencing (WGS), whole-exome sequencing (WES), virtual panels, targeted sequencing, and more. It allows for the analysis of various variant types such as SNVs, indels, short tandem repeats (STRs), copy number variants (CNVs), other structural variants, and mtDNA.

The software also facilitates the sharing of curated knowledge across a private network of labs, enhancing collaboration and knowledge reuse.

Emedgene's machine learning capabilities simplify the complex task of variant analysis, enabling labs to handle more tests daily and breaking the genomic data interpretation bottleneck.