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Author:
SGGb0nd
License:
Apache-2.0
Summary:
STEP, an acronym for Spatial Transcriptomics Embedding Procedure, is a deep learning-based tool for the analysis of single-cell RNA (scRNA-seq) and spatially resolved transcriptomics (SRT) data. STEP introduces a unified approach to process and analyze multiple samples of scRNA-seq data as well as align several sections of SRT data, disregarding location relationships. Furthermore, STEP conducts integrative analysis across different modalities like scRNA-seq and SRT.
Latest version:
0.3
Required dependencies:
einops
|
esda
|
grakel
|
leidenalg
|
libpysal
|
numpy
|
pydantic
|
scanpy
|
scikit-misc
Optional dependencies:
dgl
|
furo
|
ipykernel
|
myst-parser
|
nbsphinx
|
rpy2
|
sphinx
|
sphinx-autoapi
|
sphinx-autodoc-typehints
|
sphinx-book-theme
|
sphinx-copybutton
|
sphinxcontrib-bibtex
|
torch
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