infercnv-mcp
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Infercnv-MCP is a natural language interface for inferring Copy Number Variations (CNVs) from single-cell RNA sequencing (scRNA-Seq) data using the infercnvpy library through the Model Context Protocol (MCP).
Infercnv-MCP provides a seamless interface for researchers and developers to perform CNV analysis on scRNA-Seq data using natural language commands. It leverages the infercnvpy library, which is a powerful tool for CNV inference, and integrates it with the Model Context Protocol (MCP) to enable easy integration into various AI clients, plugins, and agent frameworks. This tool is particularly useful for researchers who want to streamline their CNV analysis workflow and for developers looking to incorporate CNV analysis capabilities into their applications. With its comprehensive modules for data input/output, preprocessing, CNV inference, and visualization, Infercnv-MCP offers a robust solution for CNV analysis. The tool supports various visualization techniques, including chromosome heatmaps, UMAP, and t-SNE, to help users interpret their data effectively. Additionally, Infercnv-MCP is designed to be user-friendly, with straightforward installation and configuration processes, making it accessible to users with varying levels of technical expertise.
Features
- IO module for reading and writing scRNA-Seq data and loading gene positions.
- Preprocessing module for neighbors computation and data preparation.
- Tool module for CNV inference and CNV score calculation.
- Plotting module for chromosome heatmaps, UMAP, and t-SNE visualizations.
- Integration with MCP for easy use in AI clients, plugins, and agent frameworks.