Use when working with MENDER (MultilayEred NeighborhooDhood-Encoded Representations), a Python tool for spatial domain identification in multiplexed imaging data. Covers spatial domain segmentation in
Use with AI
Install the MCP server or CLI to instantly fetch MENDER documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/mender
Squidpy — spatial single-cell analysis toolkit in the scverse ecosystem for analyzing and visualizing spatial molecular data. Builds spatial neighbor graphs from tissue coordinates (Visium, Xenium, ME
3 shared topics • 2 shared operations
STARmap (Spatially-resolved Transcript Amplicon Readout mapping) — in situ spatial transcriptomics method that combines hydrogel-tissue chemistry with sequencing-by-hybridization (SEDAL) for multiplex
3 shared topics • 2 shared operations
Use when working with BANKSY for spatial transcriptomics clustering that blends each cell's own expression with spatial-neighbor features. Covers SpatialExperiment and SingleCellExperiment pipelines,
2 shared topics • 2 shared operations
Cellpose — generalist deep learning algorithm for cellular and nuclear segmentation in microscopy images. Provides GPU-accelerated 2D and 3D instance segmentation using gradient flow representations,
2 shared topics • 1 shared operation
Seurat — comprehensive R toolkit for single-cell genomics enabling QC, normalization (LogNormalize, SCTransform), feature selection, dimensionality reduction (PCA, UMAP, t-SNE), graph-based clustering
2 shared topics • 1 shared operation