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github.com/aristoteleo/spateo-release @v1.1.0

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repository ↗ · DeepWiki ↗ · release v1.1.0 ↗ · + Follow
2,094 symbols 9,122 edges 222 files 1,025 documented · 49% updated 4mo agov1.1.0 · 2024-09-18★ 3421 open issues
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README

Cells do not live in a vacuum, but in a milieu defined by cell–cell communication that can be measured via emerging high-resolution spatial transcriptomics approaches. However, analytical tools that fully leverage such data for kinetic modeling remain lacking. Here we present Spateo (aristoteleo/spateo-release), a general framework for quantitative spatiotemporal modeling of single-cell resolution spatial transcriptomics. Spateo delivers novel methods for digitizing spatial layers/columns to identify spatially-polar genes, and develops a comprehensive framework of cell-cell interaction to reveal spatial effects of niche factors and cell type-specific ligand-receptor interactions. Furthermore, Spateo reconstructs 3D models of whole embryos, and performs 3D morphometric analyses. Lastly, Spateo introduces the concept of “morphometric vector field” of cell migrations, and integrates spatial differential geometry to unveil regulatory programs underlying various organogenesis patterns of Drosophila. Thus, Spateo enables the study of the ecology of organs at a molecular level in 3D space, beyond isolated single cells.

Spateo introduces a sophisticated approach, Starro, to segment single cells based purely on RNA signal, unsupervisedly identifies continuous tissue domains via spatially-constrained clustering, and dissect the intricate spatial cell type distribution and tissue composition;

Spateo identifies spatial polarity/gradient genes (e.g. neuronal layer specific genes) by solving a partial differential equation to digitize layers and columns of a spatial domain.

Spateo implements a full suite of spatially-aware modules for differential expression inference, including novel parametric models for spatially-informed prediction of cell-cell interactions and interpretable estimation of downstream effects.

Spateo enables reconstruction of 3D whole-organ models from 2D slices, identifying different “organogenesis modes” (patterns of cell migration during organogenesis) for each organ and quantifying morphometric properties (such as organ surface area, volume, length and cell density) over time.

Spateo brings in the concept of the “morphometric vector field” that predicts migration paths for each cell within an organ in a 3D fashion and reveals principles of cell migration by exploring various differential geometry quantities.

Core symbols most depended-on inside this repo

Shape

Method 1,143
Function 858
Class 91
Route 2

Languages

Python100%

Modules by API surface

spateo/alignment/methods/backend_ot.py533 symbols
spateo/alignment/methods/backend.py194 symbols
spateo/tools/CCI_effects_modeling/distributions.py90 symbols
spateo/alignment/methods/deprecated_utils.py61 symbols
spateo/plotting/static/utils.py56 symbols
spateo/external/lack.py49 symbols
spateo/tools/CCI_effects_modeling/MuSIC_downstream.py38 symbols
spateo/alignment/methods/utils.py38 symbols
spateo/configuration.py27 symbols
spateo/tools/cluster/spagcn_utils.py24 symbols
spateo/tools/CCI_effects_modeling/MuSIC.py23 symbols
spateo/plotting/static/dotplot.py23 symbols

For agents

$ claude mcp add spateo-release \
  -- python -m otcore.mcp_server <graph>

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