diff options
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-pyscenic.spec | 120 | ||||
| -rw-r--r-- | sources | 1 |
3 files changed, 122 insertions, 0 deletions
@@ -0,0 +1 @@ +/pyscenic-0.12.1.tar.gz diff --git a/python-pyscenic.spec b/python-pyscenic.spec new file mode 100644 index 0000000..652c86a --- /dev/null +++ b/python-pyscenic.spec @@ -0,0 +1,120 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pyscenic +Version: 0.12.1 +Release: 1 +Summary: Python implementation of the SCENIC pipeline for transcription factor inference from single-cell transcriptomics experiments. +License: GPL-3.0+ +URL: https://github.com/aertslab/pySCENIC +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/d2/ea/109aa69d72b54ab78eb353ddc8b6ff7e78208b5d85b7d77f5d146b78681d/pyscenic-0.12.1.tar.gz +BuildArch: noarch + +Requires: python3-ctxcore +Requires: python3-cytoolz +Requires: python3-multiprocessing-on-dill +Requires: python3-llvmlite +Requires: python3-numba +Requires: python3-attrs +Requires: python3-frozendict +Requires: python3-numpy +Requires: python3-pandas +Requires: python3-numexpr +Requires: python3-cloudpickle +Requires: python3-dask +Requires: python3-distributed +Requires: python3-arboreto +Requires: python3-boltons +Requires: python3-setuptools +Requires: python3-pyyaml +Requires: python3-tqdm +Requires: python3-interlap +Requires: python3-umap-learn +Requires: python3-loompy +Requires: python3-networkx +Requires: python3-scipy +Requires: python3-fsspec +Requires: python3-requests +Requires: python3-aiohttp +Requires: python3-scikit-learn + +%description +|buildstatus|_ |pypipackage|_ |docstatus|_ +pySCENIC is a lightning-fast python implementation of the SCENIC_ pipeline (Single-Cell rEgulatory Network Inference and +Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from +single-cell RNA-seq data. +The pioneering work was done in R and results were published in Nature Methods [1]_. +A new and comprehensive description of this Python implementation of the SCENIC pipeline is available in Nature Protocols [4]_. +pySCENIC can be run on a single desktop machine but easily scales to multi-core clusters to analyze thousands of cells +in no time. The latter is achieved via the dask_ framework for distributed computing [2]_. + +%package -n python3-pyscenic +Summary: Python implementation of the SCENIC pipeline for transcription factor inference from single-cell transcriptomics experiments. +Provides: python-pyscenic +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pyscenic +|buildstatus|_ |pypipackage|_ |docstatus|_ +pySCENIC is a lightning-fast python implementation of the SCENIC_ pipeline (Single-Cell rEgulatory Network Inference and +Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from +single-cell RNA-seq data. +The pioneering work was done in R and results were published in Nature Methods [1]_. +A new and comprehensive description of this Python implementation of the SCENIC pipeline is available in Nature Protocols [4]_. +pySCENIC can be run on a single desktop machine but easily scales to multi-core clusters to analyze thousands of cells +in no time. The latter is achieved via the dask_ framework for distributed computing [2]_. + +%package help +Summary: Development documents and examples for pyscenic +Provides: python3-pyscenic-doc +%description help +|buildstatus|_ |pypipackage|_ |docstatus|_ +pySCENIC is a lightning-fast python implementation of the SCENIC_ pipeline (Single-Cell rEgulatory Network Inference and +Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from +single-cell RNA-seq data. +The pioneering work was done in R and results were published in Nature Methods [1]_. +A new and comprehensive description of this Python implementation of the SCENIC pipeline is available in Nature Protocols [4]_. +pySCENIC can be run on a single desktop machine but easily scales to multi-core clusters to analyze thousands of cells +in no time. The latter is achieved via the dask_ framework for distributed computing [2]_. + +%prep +%autosetup -n pyscenic-0.12.1 + +%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-pyscenic -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 0.12.1-1 +- Package Spec generated @@ -0,0 +1 @@ +ccf2decf031071b8fcdb3d285f784522 pyscenic-0.12.1.tar.gz |