STARmap (Spatially-resolved Transcript Amplicon Readout mapping) — in situ spatial transcriptomics method that combines hydrogel-tissue chemistry with sequencing-by-hybridization (SEDAL) for multiplex
Use with AI
Install the MCP server or CLI to instantly fetch STARmap documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/starmap
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
3 shared topics • 2 shared operations
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
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
Spectre is an R toolkit for high-dimensional single-cell cytometry and imaging analysis, including data import (CSV/FCS), metadata integration, arcsinh/logicle transformation, clustering (FlowSOM, Phe
2 shared topics • 2 shared operations
Tangram — deep learning framework for mapping single-cell and single-nucleus gene expression data onto spatial transcriptomics data. Built on PyTorch and scanpy, Tangram optimizes a probabilistic mapp
2 shared topics • 2 shared operations