Clinical interpretation of genetic variants is a complicated process that depends on subjective judgement and unstructured evidence from research articles. This has led to variations in conclusions between laboratories, in some cases with serious medical consequences.
ELLA aims to reduce variability by guiding the interpreter through the various steps of an assessment based on ACMG-AMP guidelines, while simultaneously translating key facts into a format suitable for data processing. This makes it possible to automate parts of the process and suggest conclusions for the user. In addition, the justification for each assessment becomes more transparent, standardized and reproducible, which is crucial for reuse and sharing of results with other laboratories.
Information security and patient safety is at the core of ELLA, with a design that allows running in an air-gapped environment when necessary. The workflow encourages peer review of all variants of medical significance, and a complete history is kept of all changes.
Flexible workflow with categorized team work lists. Variants or samples, quick or thorough interpretation.
Advanced pre-filtering and on-the-fly tagging, including support for family data.
Retrieval and thorough evaluation of annotation and literature references.
Suggested criteria and variant classification based on ACMG-AMP guidelines.
Visualization of raw data (bam), structural data and user added tracks using igv.js.
Complete documentation and history of variant evaluations.
Advanced report generation using Apache Superset.
Open source code, available under MIT licence. Visit our GitLab repository!
ELLA development team | Department of Medical Genetics | Oslo University Hospital | Norway