Statistical Methods and Software for Spatial Proteomics in Cancer Research
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Are you interested in spatial proteomics?
Join this webinar as NCI grantee, Dr. Brooke Fridley, walks you through the analysis methods and statistical tools her lab has built to analyze spatial proteomic data sets and what that has revealed about immune cells behavior in ovarian cancer tumors.
During the webinar, you will hear about these NCI-funded R-based analysis tools:
- spatialTIME: Visualize and analyze the spatial architecture of the tumor immune microenvironment with multiplex immunofluorescence data.
- mxfda: Perform functional data analysis for single-cell spatial data.
- scSpatialSim: Simulate single-cell molecular spatial patterns without requiring reference data sets.
- BTIME: Assess the relationship between specific cell populations and a predictor or exposure variable by fitting Bayesian hierarchical beta-binomial models to the data.
Whether you study cancer biology or focus on data science, this webinar offers practical tools and insights you can apply to your work.
NCI’s Informatics Technology for Cancer Research (ITCR) program has also funded Dr. Fridley’s and her lab’s work to develop analytical tools to study the tumor microenvironment leveraging spatial transcriptomics.
Speaker Bio
Brooke L. Fridley, Ph.D.
Dr. Fridley is Division Director for Health Services and Outcomes Research in the Department of Pediatrics, Associate Chair for Research for the Department of Pediatrics, and Director of the Biostatistics and Computational Biology Core at Children's Mercy Research Institute. She specializes in developing statistical methods and software to tackle complex challenges in oncology research, with a current focus on spatial transcriptomic and proteomic technologies.