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๐Ÿ—‚๏ธ Mastering Spatial Analysis of Multiplex Imaging Data with SCIMAP


This series is designed to equip researchers, data scientists, and enthusiasts with the knowledge and tools necessary to unlock the full potential of spatial analysis techniques. Whether you're new to the field or looking to deepen your understanding, these tutorials will guide you through the intricacies of analyzing complex imaging data, enabling you to uncover the spatial relationships and patterns that lie within.

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Set up

๐Ÿค– Install Scimap
๐Ÿ“ฅ Download demo data
๐Ÿ“ Prepare demo data for analysis

Cell Phenotyping

๐Ÿคน๐Ÿผโ€โ™‚๏ธ Phenotype cells by unsupervised clustering
๐Ÿ‘ฝ Phenotype cells using a hierarchical probabilistic model
๐Ÿ™Œ Add Regions of Interest (ROIs) for exploration
๐Ÿคฉ Explore the composition of defined cell types between samples and ROIs

Spatial Analysis

๐Ÿ“ Calculate and visualize distances between cell types
๐Ÿค Cell-cell interaction/ co-occurrence analysis
โš–๏ธ Compare proximity scores between samples
๐Ÿ”ญ Search for spatial patterns

Cellular Neighbourhoods

๐ŸŒณ Compute neighborhoods using cell-type or cluster information (includes LDA method)
๐Ÿš€ Compute neighborhoods using expression data

Export and Helper Functions

โฌ‡๏ธ Export analysis results to .csv
๐Ÿ‘ฉโ€๐ŸŽจ Animate with scimap
๐Ÿ‘‘ Merge objects, Classify cells etc..

Videos

๐ŸŽฅ Video tutorials