Variant Interpretation

Problem

As a genomics service provider building your clinical decision support tool to assist in the interpretation of genetic variants for early cancer prognosis and therapy, you have access to patient genomic profiles but need help integrating and augmenting this data with relevant clinical databases (e.g., ClinVar, Cosmic, PubMed) and developing algorithms to prioritise these variants based on causality and actionability.

What can we offer

gt-omics will offer a targeted approach to develop and extend the clinical genetics decision support pipeline

This approach can contain:

• Data Source Integration: Linking patient genomic data with clinical databases and literature to build a comprehensive variant interpretation framework.

• Algorithm Development: Designing and implementing machine learning algorithms to prioritise genetic variants based on pathogenicity, using both in-house and public data.

• Product Definition: Supporting the product team to outline the core features and functionalities that make best use of all available data, ensuring a focused and efficient development process.

• Pipeline development: Working with the development and DevOps team to deploy the solution to handle the computational load of genomic data processing and algorithm execution.

• Prototype and Documentation: Creating a prototype of the decision support tool, accompanied by detailed documentation for future development and integration.