SINFONIA: scalable identification of spatially variable genes for deciphering spatial domains

Find more details on the Documentation of SINFONIA.

Installation

SINFONIA is available on PyPI here and can be installed via

pip install sinfonia

You can also install SINFONIA from GitHub via

git clone git://github.com/BioX-NKU/SINFONIA.git
cd SINFONIA
python setup.py install

The dependencies will be automatically installed along with SINFONIA.

Quick Start

Input

• adata: AnnData object of shape n_obs × n_vars. Rows correspond to cells and columns to genes.
• mode: Mode for identifying spatially variable genes. By default, mode='moran_geary'.
• n_top_genes: Number of spatially variable genes to keep. By default, n_top_genes=2000.

Output

• adata: AnnData object with identified spatially variable genes and additional fields.

SINFONIA can also be seamlessly integrated with SCANPY, a widely-used Python library for single-cell data analysis.

	import scanpy as sc
	import sinfonia
	# Load the spatial transcriptomic data as an AnnData object (adata)
	# Normalize and logarithmize if the data contains raw counts
	sc.pp.normalize_total(adata)
	sc.pp.log1p(adata)
	# Run SINFONIA
	adata = sinfonia.spatially_variable_genes(adata)

Documentation notebook

We provide a quick-start notebook which describes the fundamentals in detail and reproduces the results of SINFONIA. We also provide rich documentation in the form of functional application programming interface documentation, tutorials and example workflows.