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GSVA: Optimizing Gene Set Variation Analysis for Single-Cell Data
To optimize GSVA functionality to analyze single-cell and spatial transcriptomic data sets, increasing its robustness and scalability and improving user interface and documentation.
GSVA is an R/Bioconductor package that enables pathway-centric analyses of data produced by high-throughput molecular profiling technologies such as microarrays, RNA sequencing, NanoString, and mass spectrometry. GSVA has the potential to be used to perform single-cell molecular profiling, but direct use is currently limited to datasets with a few thousand cells. This project will use best practices in software development to enable GSVA analysis on larger datasets, enable analysis of spatial transcriptomics data, and increase the robustness and efficiency of GSVA.