This page includes demonstration versions of many of the visualization and analytics tools that our team is working on. For in-house use by out research team, many of these tools are designed to interface with an SQL database. But as we develop more robust versions of each tool, our goal is to create standalone versions that read user-supplied CSV files. These standalone tools will be added to the BOSS suite of tools when they are ready for public use.
All visualizations are designed to run in Google Chrome. Other browsers are not supported and may not render properly.
These charts are designed to make it easier to explore, visualize and compare the expression of genes that are relevant to cancer biology and immunotherapy. High-throughput genomic, transcriptomic and proteomic sequencing are playing an increasingly important role in both cancer research and personalized medicine. We are exploring new approaches for simplifying the user interface with these data sets. Specifically, we are building networks of functionally-related gene clusters that are accessed via an intuitive visual interface. We are integrating data sets from both public sources (NCBI, TCGA) and in-house, proprietary data sets.
he BOSS Relationships tool analyzes the correlations between biomarkers and outcomes, and analyzes their predictive reliability. The BOSS Relationships tool generates an interactive Scatter Chart. Use of these visualization does not require any special software, just a compatible web browser (Google Chrome). For more information on how to use these software tools refer to the Instructions located on the BOSS page.
The BOSS Comparisons tool analyzes how parameters differ between cohorts of patients. The BOSS Comparisons tool generates an interactive Bar Chart. Use of these visualization does not require any special software, just a compatible web browser (Google Chrome). For more information on how to use these software tools refer to the Instructions located on the BOSS page.
The ability to monitor how individual patients are responding to cancer immunotherapy is essential for personalizing treatment and improving outcomes. We have been working to develop tools that facilitate a detailed analysis of how a patient’s peripheral immune profile changes over the course of an immunotherapy treatment. Here, we have included demonstration versions of these efforts. Specifically, we are developing tools to analyze:
- Changes in frequency of peripheral leukocytes.
- Distribution of biomarker and drug target expresssion among peripheral leukocyte populations.
- Changes in serum cytokine and chemokine concentrations.
- Changes in CBC and Blood Chemistry parameters.