%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
* Tue May 30 2023 Python_Bot <Python_Bot@openeuler.org> - 0.12.1-1
- Package Spec generated