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|
%global _empty_manifest_terminate_build 0
Name: python-SpaDecon
Version: 1.1.2
Release: 1
Summary: SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning
License: MIT License
URL: https://github.com/kylepcoleman87/SpaDecon
Source0: https://mirrors.aliyun.com/pypi/web/packages/fa/a0/96e2f8fba0e577948f7e7e948f31aa619968bd1ce0861f94ff392c341826/SpaDecon-1.1.2.tar.gz
BuildArch: noarch
Requires: python3-keras
Requires: python3-pandas
Requires: python3-numpy
Requires: python3-scipy
Requires: python3-scanpy
Requires: python3-anndata
Requires: python3-sklearn
Requires: python3-tensorflow
%description
# SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning
### Kyle Coleman, Jian Hu, Amelia Schroeder, Edward B. Lee, Mingyao Li*
SpaDecon is a semi-supervised learning-based method developed to perform cell-type deconvolution on spatially resolved transcriptomics (SRT) datasets. SpaDecon has been shown to provide accurate cell-type deconvolution results for both Spatial Transcriptomics (ST) and 10X Visium SRT datasets. Annotated scRNA-seq gene expression data from the same type of tissue as the SRT data are required for deconvolution.
## SpaDecon Installation
- SpaDecon installation requires a python version of at least 3.6. The version of python can be checked by:
```python
import platform
platform.python_version()
```
'3.7.11'
We recommend creating and activating a new conda environment when installing the SpaDecon package. For instance,
```bash
conda create -n SpaDecon python=3.7
conda activate SpaDecon
```
There are mulitple ways to install SpaDecon:
- Install SpaDecon using PyPI:
```bash
pip3 install SpaDecon
```
- Download and install SpaDecon package from GitHub:
```bash
git clone https://github.com/kpcoleman/SpaDecon
cd SpaDecon/
python3 setup.py install --user
```
## Tutorial
A markdown tutorial file can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/Tutorial.md
A tutorial in the form of a jupyter notebook can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/tutorial.ipynb
## Software Requirements
python >= 3.6
keras==2.2.4
pandas==1.2.4
numpy==1.20.1
scipy==1.6.2
scanpy==1.7.0
anndata==0.7.6
sklearn
tensorflow==1.14.0
%package -n python3-SpaDecon
Summary: SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning
Provides: python-SpaDecon
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-SpaDecon
# SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning
### Kyle Coleman, Jian Hu, Amelia Schroeder, Edward B. Lee, Mingyao Li*
SpaDecon is a semi-supervised learning-based method developed to perform cell-type deconvolution on spatially resolved transcriptomics (SRT) datasets. SpaDecon has been shown to provide accurate cell-type deconvolution results for both Spatial Transcriptomics (ST) and 10X Visium SRT datasets. Annotated scRNA-seq gene expression data from the same type of tissue as the SRT data are required for deconvolution.
## SpaDecon Installation
- SpaDecon installation requires a python version of at least 3.6. The version of python can be checked by:
```python
import platform
platform.python_version()
```
'3.7.11'
We recommend creating and activating a new conda environment when installing the SpaDecon package. For instance,
```bash
conda create -n SpaDecon python=3.7
conda activate SpaDecon
```
There are mulitple ways to install SpaDecon:
- Install SpaDecon using PyPI:
```bash
pip3 install SpaDecon
```
- Download and install SpaDecon package from GitHub:
```bash
git clone https://github.com/kpcoleman/SpaDecon
cd SpaDecon/
python3 setup.py install --user
```
## Tutorial
A markdown tutorial file can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/Tutorial.md
A tutorial in the form of a jupyter notebook can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/tutorial.ipynb
## Software Requirements
python >= 3.6
keras==2.2.4
pandas==1.2.4
numpy==1.20.1
scipy==1.6.2
scanpy==1.7.0
anndata==0.7.6
sklearn
tensorflow==1.14.0
%package help
Summary: Development documents and examples for SpaDecon
Provides: python3-SpaDecon-doc
%description help
# SpaDecon: cell-type deconvolution in spatial transcriptomics with semi-supervised learning
### Kyle Coleman, Jian Hu, Amelia Schroeder, Edward B. Lee, Mingyao Li*
SpaDecon is a semi-supervised learning-based method developed to perform cell-type deconvolution on spatially resolved transcriptomics (SRT) datasets. SpaDecon has been shown to provide accurate cell-type deconvolution results for both Spatial Transcriptomics (ST) and 10X Visium SRT datasets. Annotated scRNA-seq gene expression data from the same type of tissue as the SRT data are required for deconvolution.
## SpaDecon Installation
- SpaDecon installation requires a python version of at least 3.6. The version of python can be checked by:
```python
import platform
platform.python_version()
```
'3.7.11'
We recommend creating and activating a new conda environment when installing the SpaDecon package. For instance,
```bash
conda create -n SpaDecon python=3.7
conda activate SpaDecon
```
There are mulitple ways to install SpaDecon:
- Install SpaDecon using PyPI:
```bash
pip3 install SpaDecon
```
- Download and install SpaDecon package from GitHub:
```bash
git clone https://github.com/kpcoleman/SpaDecon
cd SpaDecon/
python3 setup.py install --user
```
## Tutorial
A markdown tutorial file can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/Tutorial.md
A tutorial in the form of a jupyter notebook can be found here: https://github.com/kpcoleman/SpaDecon/blob/main/tutorial/tutorial.ipynb
## Software Requirements
python >= 3.6
keras==2.2.4
pandas==1.2.4
numpy==1.20.1
scipy==1.6.2
scanpy==1.7.0
anndata==0.7.6
sklearn
tensorflow==1.14.0
%prep
%autosetup -n SpaDecon-1.1.2
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-SpaDecon -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.2-1
- Package Spec generated
|
