GENOMANALYTICS
GenomAnalytics (GA) is a visualization and statistical analysis tool composed of flexible, reusable widgets. It utilizes GenomOncology's Knowledge Management System 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.
Integrated Data
Our tool supports the visualization of survival data through Kaplan-Meier graphs. Clinicians can analyze an individual case's survival or the aggregated set of data for larger cohorts.
Survival Analysis
GenomAnalytics allows you to group different filter sets and/or different cases together in order to conduct in-depth cluster analysis on either a wide or specific data set.
Cluster Analysis
Advanced Filtering
Our tool empowers you to be able to filter through multiple data sets using boolean logic statements and/or a combination of different clinical and molecular variables easily.
Configurable Dashboards
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.
Sophisticated Analysis
Our tool has a simple, easy UI that enables you to configure the solution to your needs. For more sophisticated analyses, our tool also integrates with your Jupyter notebooks and R data tools.
OUR CAPABILITIES
SURVIVAL ANALYSIS
Our Knowledge Management System 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.
ALTERATION OCCURRENCE
PATTERNS
GenomAnalytics can help users determine recurring, co-occurring, and mutually exclusive alterations. Molecular data loaded into the KMS 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.
