GenomAnalytics (GA) is a visualization and statistical analysis tool composed of flexible, reusable widgets. It utilizes GenomOncology's Precision Oncology Platform to enable the analysis of any molecular, clinical, demographic, or recommendation data in one view. The tool also integrates with any existing R/ Python-based tools and Jupyter Notebooks. GenomAnalytics provides you with a fully configurable visual dashboard to make analyzing and reviewing large sets of data for audits and research more efficient.
We help you visualize and analyze your molecular and clinical patient data in one place.
WHAT WE ENABLE YOU TO DO
We can easily combine your clinical and molecular data to allow you to visualize and analyze comprehensive summaries of all of your data in one or more dashboards.
Our tool enables you to review cohorts of patients that can be identified for enhancing clinical trial enrollment, or matching to a new approved therapy.
GenomAnalytics allows you to identify top clinical trials matched for your patient population, including top triggering biomarkers and institution-specific or geo-located trials.
The solution enables you to gain insights into laboratory operational metrics, such as turnaround time, number of cases per month, and sign-out numbers per user.
GenomAnalytics allows you to create your own configurable dashboards with user-specified graphs and modals that will automatically update based on new clinical or molecular data.
Our tool has a simple, easy UI that enables you to configure the solution to fit your needs. For more sophisticated analyses, our tool also integrates with your Jupyter notebooks and R data tools.
Our Precision Oncology Platform can handle uploaded event data, such as time to progression, time to death, or time to the last follow-up. GenomAnalytics uses this data to perform survival analysis on different case cohorts and determine survival differences between each group. Results can be displayed as Kaplan-Meier curves or as survival summaries.
GenomAnalytics can help users determine recurring, co-occurring, and mutually exclusive alterations. Molecular data loaded into the Precision Oncology Platform can be compared across case cohorts and our built-in comparison tools allow users to easily determine alteration occurrence patterns across cohorts and different disease types.