Metadata-Version: 2.1
Name: sdeper
Version: 1.6.1
Summary: Spatial Deconvolution method with Platform Effect Removal
Home-page: https://az7jh2.github.io/SDePER/
Author: Ningshan Li
Author-email: hill103.2@gmail.com
Project-URL: Documentation, https://sdeper.readthedocs.io/en/latest/
Project-URL: Source, https://github.com/az7jh2/SDePER
Project-URL: Changelog, https://sdeper.readthedocs.io/en/latest/changelog.html
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Operating System :: POSIX :: Linux
Requires-Python: >=3.9.12, <3.11
Description-Content-Type: text/markdown
Requires-Dist: numpy==1.22.4
Requires-Dist: scipy==1.8.1
Requires-Dist: pandas==1.4.3
Requires-Dist: networkx==2.8.4
Requires-Dist: matplotlib==3.5.2
Requires-Dist: scikit-learn==1.1.1
Requires-Dist: numba==0.55.2
Requires-Dist: openpyxl==3.0.10
Requires-Dist: tensorflow-cpu==2.9.1
Requires-Dist: scanpy==1.9.1
Requires-Dist: scikit-misc==0.1.4
Requires-Dist: seaborn==0.11.2
Requires-Dist: umap-learn==0.5.3
Requires-Dist: distinctipy==1.2.2
Requires-Dist: reportlab==4.1.0
Requires-Dist: opencv-python-headless==4.6.0.66

# SDePER
![OS](https://img.shields.io/badge/os-linux-blue) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/sdeper)](https://www.python.org/) [![GitHub release (latest by date)](https://img.shields.io/github/v/release/az7jh2/SDePER)](https://github.com/az7jh2/SDePER) [![PyPI](https://img.shields.io/pypi/v/sdeper)](https://pypi.org/project/sdeper/)  [![Conda Version](https://img.shields.io/conda/vn/bioconda/sdeper)](https://anaconda.org/bioconda/sdeper) [![Docker Image Version (latest by date)](https://img.shields.io/docker/v/az7jh2/sdeper?label=docker)](https://hub.docker.com/r/az7jh2/sdeper) [![Read the Docs (version)](https://img.shields.io/readthedocs/sdeper/latest)](https://sdeper.readthedocs.io/en/latest/)

**SDePER** (**S**patial **De**convolution method with **P**latform **E**ffect **R**emoval) is a **hybrid** machine learning and regression method to deconvolve Spatial barcoding-based transcriptomic data using reference single-cell RNA sequencing data, considering **platform effects removal**, **sparsity** of cell types per capture spot and across-spots **spatial correlation** in cell type compositions. SDePER is also able to **impute** cell type compositions and gene expression at unmeasured locations in a tissue map with **enhanced resolution**.

## Quick Start

SDePER currently supports only Linux operating systems such as Ubuntu, and is compatible with Python versions 3.9.12 up to but not including 3.11.

SDePER can be installed via conda

```bash
conda create -n sdeper-env -c bioconda -c conda-forge python=3.9.12 sdeper
```

or pip

```bash
conda create -n sdeper-env python=3.9.12
conda activate sdeper-env
pip install sdeper
```

SDePER requires **4 input files** for cell type deconvolution:

1. raw nUMI counts of **spatial transcriptomics data** (spots × genes): `spatial.csv`
2. raw nUMI counts of **reference scRNA-seq data** (cells × genes): `scrna_ref.csv`
3. **cell type annotations** for all cells in scRNA-seq data (cells × 1): `scrna_anno.csv`
4. **adjacency matrix** of spots in spatial transcriptomics data (spots × spots): `adjacency.csv`

To start cell type deconvolution by running

```bash
runDeconvolution -q spatial.csv -r scrna_ref.csv -c scrna_anno.csv -a adjacency.csv
```

**Homepage**: [https://az7jh2.github.io/SDePER/](https://az7jh2.github.io/SDePER/).

**Full Documentation** for SDePER is available on [Read the Docs](https://sdeper.readthedocs.io/en/latest/).

**Example data and Analysis** using SDePER are available in our GitHub repository [SDePER_Analysis](https://github.com/az7jh2/SDePER_Analysis).
