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author | CoprDistGit <infra@openeuler.org> | 2023-06-20 08:04:40 +0000 |
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committer | CoprDistGit <infra@openeuler.org> | 2023-06-20 08:04:40 +0000 |
commit | 20f4b1ec3044ff07beaf8426f4e3254ae0d00cea (patch) | |
tree | 898a86e038bf8d3d83949f759885d7fa79afd1f2 | |
parent | 5bce4e2b56889ab26cfaa7551c573211e123bc7b (diff) |
automatic import of python-spacemakeopeneuler20.03
-rw-r--r-- | .gitignore | 1 | ||||
-rw-r--r-- | python-spacemake.spec | 147 | ||||
-rw-r--r-- | sources | 1 |
3 files changed, 149 insertions, 0 deletions
@@ -0,0 +1 @@ +/spacemake-0.7.2.tar.gz diff --git a/python-spacemake.spec b/python-spacemake.spec new file mode 100644 index 0000000..edd4a05 --- /dev/null +++ b/python-spacemake.spec @@ -0,0 +1,147 @@ +%global _empty_manifest_terminate_build 0 +Name: python-spacemake +Version: 0.7.2 +Release: 1 +Summary: A bioinformatic pipeline for the analysis of spatial transcriptomic data +License: GPL +URL: https://github.com/rajewsky-lab/spacemake +Source0: https://mirrors.aliyun.com/pypi/web/packages/fb/22/98eb4954a6ca3e55904ae0cac75d64a75b93aec06096a496a909bcc95269/spacemake-0.7.2.tar.gz +BuildArch: noarch + + +%description +<a href="https://pypi.org/project/spacemake/"> + <img src="https://img.shields.io/pypi/v/spacemake.svg" / ></a> + +<a href="https://spacemake.readthedocs.io/"> + <img src="https://readthedocs.org/projects/spacemake/badge/?version=latest" / ></a> + + <a href="https://pepy.tech/project/spacemake"> + <img src="https://pepy.tech/badge/spacemake" / ></a> + +# Spacemake: processing and analysis of large-scale spatial transcriptomics data + +<img src="https://raw.githubusercontent.com/rajewsky-lab/spacemake/master/docs/graphical_abstract_twitter.png" width="400" /> + +Spacemake is a modular, robust, and scalable spatial transcriptomics pipeline built in `Snakemake` and `Python`. Spacemake is designed to handle all major spatial transcriptomics datasets and can be readily configured for other technologies. It can process and analyze several samples in parallel, even if they stem from different experimental methods. Spacemake's unified framework enables reproducible data processing from raw sequencing data to automatically generated downstream analysis reports. Spacemake is built with a modular design and offers additional functionality such as sample merging, saturation analysis, and analysis of long reads as separate modules. + +If you find Spacemake useful in your work, consider citing it: + +``` +Spacemake: processing and analysis of large-scale spatial transcriptomics data +Tamas Ryszard Sztanka-Toth, Marvin Jens, Nikos Karaiskos, Nikolaus Rajewsky +GigaScience, Volume 11, 2022, giac064 +``` + +Documentation can be found [here](https://spacemake.readthedocs.io/en/latest/). + + + +%package -n python3-spacemake +Summary: A bioinformatic pipeline for the analysis of spatial transcriptomic data +Provides: python-spacemake +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-spacemake +<a href="https://pypi.org/project/spacemake/"> + <img src="https://img.shields.io/pypi/v/spacemake.svg" / ></a> + +<a href="https://spacemake.readthedocs.io/"> + <img src="https://readthedocs.org/projects/spacemake/badge/?version=latest" / ></a> + + <a href="https://pepy.tech/project/spacemake"> + <img src="https://pepy.tech/badge/spacemake" / ></a> + +# Spacemake: processing and analysis of large-scale spatial transcriptomics data + +<img src="https://raw.githubusercontent.com/rajewsky-lab/spacemake/master/docs/graphical_abstract_twitter.png" width="400" /> + +Spacemake is a modular, robust, and scalable spatial transcriptomics pipeline built in `Snakemake` and `Python`. Spacemake is designed to handle all major spatial transcriptomics datasets and can be readily configured for other technologies. It can process and analyze several samples in parallel, even if they stem from different experimental methods. Spacemake's unified framework enables reproducible data processing from raw sequencing data to automatically generated downstream analysis reports. Spacemake is built with a modular design and offers additional functionality such as sample merging, saturation analysis, and analysis of long reads as separate modules. + +If you find Spacemake useful in your work, consider citing it: + +``` +Spacemake: processing and analysis of large-scale spatial transcriptomics data +Tamas Ryszard Sztanka-Toth, Marvin Jens, Nikos Karaiskos, Nikolaus Rajewsky +GigaScience, Volume 11, 2022, giac064 +``` + +Documentation can be found [here](https://spacemake.readthedocs.io/en/latest/). + + + +%package help +Summary: Development documents and examples for spacemake +Provides: python3-spacemake-doc +%description help +<a href="https://pypi.org/project/spacemake/"> + <img src="https://img.shields.io/pypi/v/spacemake.svg" / ></a> + +<a href="https://spacemake.readthedocs.io/"> + <img src="https://readthedocs.org/projects/spacemake/badge/?version=latest" / ></a> + + <a href="https://pepy.tech/project/spacemake"> + <img src="https://pepy.tech/badge/spacemake" / ></a> + +# Spacemake: processing and analysis of large-scale spatial transcriptomics data + +<img src="https://raw.githubusercontent.com/rajewsky-lab/spacemake/master/docs/graphical_abstract_twitter.png" width="400" /> + +Spacemake is a modular, robust, and scalable spatial transcriptomics pipeline built in `Snakemake` and `Python`. Spacemake is designed to handle all major spatial transcriptomics datasets and can be readily configured for other technologies. It can process and analyze several samples in parallel, even if they stem from different experimental methods. Spacemake's unified framework enables reproducible data processing from raw sequencing data to automatically generated downstream analysis reports. Spacemake is built with a modular design and offers additional functionality such as sample merging, saturation analysis, and analysis of long reads as separate modules. + +If you find Spacemake useful in your work, consider citing it: + +``` +Spacemake: processing and analysis of large-scale spatial transcriptomics data +Tamas Ryszard Sztanka-Toth, Marvin Jens, Nikos Karaiskos, Nikolaus Rajewsky +GigaScience, Volume 11, 2022, giac064 +``` + +Documentation can be found [here](https://spacemake.readthedocs.io/en/latest/). + + + +%prep +%autosetup -n spacemake-0.7.2 + +%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-spacemake -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.2-1 +- Package Spec generated @@ -0,0 +1 @@ +dbf82226a92609ca245f89a8fc17fe74 spacemake-0.7.2.tar.gz |