diff options
Diffstat (limited to 'python-imap.spec')
| -rw-r--r-- | python-imap.spec | 129 |
1 files changed, 129 insertions, 0 deletions
diff --git a/python-imap.spec b/python-imap.spec new file mode 100644 index 0000000..b1caa66 --- /dev/null +++ b/python-imap.spec @@ -0,0 +1,129 @@ +%global _empty_manifest_terminate_build 0 +Name: python-imap +Version: 1.0.0 +Release: 1 +Summary: The integration of single-cell RNA-sequencing datasets from multiple sources is critical for deciphering cell-cell heterogeneities and interactions in complex biological systems. We present a novel unsupervised batch removal framework, called iMAP, based on two state-of-art deep generative models – autoencoders and generative adversarial networks. +License: MIT Licence +URL: https://github.com/Svvord/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/8f/39/7c78f15ed87edf30277c474a2823dcdf79e8416c044b8ba46e5204c9a6fc/imap-1.0.0.tar.gz +BuildArch: noarch + + +%description +# iMAP - Integration of multiple single-cell datasets by adversarial paired transfer networks + +### Installation + +#### 1. Prerequisites + +<ul> + <li>Install Python >= 3.6. Typically, you should use the Linux system and install a newest version of <a href='https://www.anaconda.com/'>Anaconda</a> or <a href = 'https://docs.conda.io/en/latest/miniconda.html'> Miniconda </a>.</li> + <li>Install pytorch >= 1.1.0. To obtain the optimal performance of deep learning-based models, you should have a Nivdia GPU and install the appropriate version of CUDA. (We tested with CUDA = 9.0)</li> + <li> Install scanpy >= 1.5.1 for pre-processing. </li> + <li>(Optional) Install <a href='https://github.com/slundberg/shap'>SHAP</a> for interpretation.</li> +</ul> + +#### 2. Installation + +The iMAP python package is available for pip install(`pip install imap`). The functions required for the stage I and II of iMAP could be imported from “imap.stage1” and “imap.stage2”, respectively. + +### Tutorials + +Tutorials and API reference are available in the <a href='tutorials'>tutorials directory</a>. + +%package -n python3-imap +Summary: The integration of single-cell RNA-sequencing datasets from multiple sources is critical for deciphering cell-cell heterogeneities and interactions in complex biological systems. We present a novel unsupervised batch removal framework, called iMAP, based on two state-of-art deep generative models – autoencoders and generative adversarial networks. +Provides: python-imap +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-imap +# iMAP - Integration of multiple single-cell datasets by adversarial paired transfer networks + +### Installation + +#### 1. Prerequisites + +<ul> + <li>Install Python >= 3.6. Typically, you should use the Linux system and install a newest version of <a href='https://www.anaconda.com/'>Anaconda</a> or <a href = 'https://docs.conda.io/en/latest/miniconda.html'> Miniconda </a>.</li> + <li>Install pytorch >= 1.1.0. To obtain the optimal performance of deep learning-based models, you should have a Nivdia GPU and install the appropriate version of CUDA. (We tested with CUDA = 9.0)</li> + <li> Install scanpy >= 1.5.1 for pre-processing. </li> + <li>(Optional) Install <a href='https://github.com/slundberg/shap'>SHAP</a> for interpretation.</li> +</ul> + +#### 2. Installation + +The iMAP python package is available for pip install(`pip install imap`). The functions required for the stage I and II of iMAP could be imported from “imap.stage1” and “imap.stage2”, respectively. + +### Tutorials + +Tutorials and API reference are available in the <a href='tutorials'>tutorials directory</a>. + +%package help +Summary: Development documents and examples for imap +Provides: python3-imap-doc +%description help +# iMAP - Integration of multiple single-cell datasets by adversarial paired transfer networks + +### Installation + +#### 1. Prerequisites + +<ul> + <li>Install Python >= 3.6. Typically, you should use the Linux system and install a newest version of <a href='https://www.anaconda.com/'>Anaconda</a> or <a href = 'https://docs.conda.io/en/latest/miniconda.html'> Miniconda </a>.</li> + <li>Install pytorch >= 1.1.0. To obtain the optimal performance of deep learning-based models, you should have a Nivdia GPU and install the appropriate version of CUDA. (We tested with CUDA = 9.0)</li> + <li> Install scanpy >= 1.5.1 for pre-processing. </li> + <li>(Optional) Install <a href='https://github.com/slundberg/shap'>SHAP</a> for interpretation.</li> +</ul> + +#### 2. Installation + +The iMAP python package is available for pip install(`pip install imap`). The functions required for the stage I and II of iMAP could be imported from “imap.stage1” and “imap.stage2”, respectively. + +### Tutorials + +Tutorials and API reference are available in the <a href='tutorials'>tutorials directory</a>. + +%prep +%autosetup -n imap-1.0.0 + +%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-imap -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.0-1 +- Package Spec generated |