Core 2: Computational and Data Integration

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COMPUTATIONAL AND DATA INTEGRATION CORE SUMMARY The primary objective of Core C is to strengthen the New York University Langone Health (NYULH) Metastasis Research Network Center’s research goals by providing standardized, robust, and harmonized workflows to acquire, analyze, integrate, visualize and share data from single cell RNA sequencing, spatial transcriptomics, digital spatial profiling and highly multiplexed microscopy platforms that are utilized by all three research projects and Core B. Core C will build on multi-dimensional molecular and tissue histology data that are generated with specimens obtained from both genetically engineered melanoma mouse models and patient specimens to: 1) develop and use a computational analysis pipeline that is robust, transparent, reproducible and scalable; 2) integrate metastasis driving molecular features of melanoma cells, stromal fibroblasts and lymph-nodes in space and time with data from complementary technology platforms; and 3) build a web based dashboard that will allow basic scientists and clinicians to analyze, explore and visualize this complex molecular and spatial information in an intuitive and meaningful way. We envision that our robust data analysis pipelines and interactive data visualization platforms will foster inter- disciplinary collaborations within the larger metastasis field and spark new ideas to strengthen our understanding of early tumor cell dissemination, cross talk between tumor cells and their cellular and molecular microenvironments and determinants of melanoma metastasis and metastatic cancer progression in general.