diff options
| author | CoprDistGit <infra@openeuler.org> | 2023-05-15 07:09:57 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2023-05-15 07:09:57 +0000 |
| commit | 2766c86de1b8065e5f75101f1ba14b1bfac75381 (patch) | |
| tree | 0157892a254c2c7152fdf5520d3ca0eab4684ec3 | |
| parent | 220ca167cfc2b89f3084b5668586eee5f98fe8a8 (diff) | |
automatic import of python-chromosight
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-chromosight.spec | 499 | ||||
| -rw-r--r-- | sources | 1 |
3 files changed, 501 insertions, 0 deletions
@@ -0,0 +1 @@ +/chromosight-1.6.3.tar.gz diff --git a/python-chromosight.spec b/python-chromosight.spec new file mode 100644 index 0000000..92b895d --- /dev/null +++ b/python-chromosight.spec @@ -0,0 +1,499 @@ +%global _empty_manifest_terminate_build 0 +Name: python-chromosight +Version: 1.6.3 +Release: 1 +Summary: Detect loops (and other patterns) in Hi-C contact maps. +License: MIT +URL: https://github.com/koszullab/chromosight +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/e5/a6/302010f5ec174023ae984e5cb76413a7cb7129a19f8b7e503699da14c52a/chromosight-1.6.3.tar.gz +BuildArch: noarch + +Requires: python3-cooler +Requires: python3-docopt +Requires: python3-jsonschema +Requires: python3-matplotlib +Requires: python3-numpy +Requires: python3-scikit-learn +Requires: python3-scipy + +%description +# Chromosight +<img src="docs/logo/chromosight.gif" alt="animated logo" width="200"/> + +[](https://badge.fury.io/py/chromosight) [](http://bioconda.github.io/recipes/chromosight/README.html) [](https://github.com/koszullab/chromosight/actions/workflows/build.yml) [](https://quay.io/repository/biocontainers/chromosight) [](https://codecov.io/gh/koszullab/chromosight) [](https://chromosight.readthedocs.io) [](https://opensource.org/licenses/GPL-3.0) [](https://lgtm.com/projects/g/koszullab/chromosight/context:python) + +Python package to detect chromatin loops (and other patterns) in Hi-C contact maps. + +* Associated publication: https://www.nature.com/articles/s41467-020-19562-7 +* Documentation and analyses examples: https://chromosight.readthedocs.io +* scripts used for the analysis presented in the article https://github.com/koszullab/chromosight_analyses_scripts + +## Installation + +Stable version with pip: + +```sh +pip3 install --user chromosight +``` +Stable version with conda: +```sh +conda install -c bioconda -c conda-forge chromosight +``` + +or, if you want to get the latest development version: + +``` +pip3 install --user -e git+https://github.com/koszullab/chromosight.git@master#egg=chromosight +``` + +## Usage + +The two main subcommands of `chromosight` are `detect` and `quantify`. For more advanced use, there are two additional subcomands: `generate-config` and `list-kernels`. To get the list and description of those subcommands, you can always run: + +```bash +chromosight --help +``` +Pattern detection is done using the `detect` subcommand. The `quantify` subcommand is used to compute pattern matching scores for a list of 2D coordinates on a Hi-C matrix. The `generate-config` subcommand is used to create a new type of pattern that can then be fed to `detect` using the `--custom-kernel` option. The `list-kernels` command is used to view informations about the available patterns. + +### Get started +To get a first look at a chromosight run, you can run `chromosight test`, which will download a test dataset from the github repository and run `chromosight detect` on it. You can then have a look at the output files generated. + +### Important options + +When running `chromosight detect`, there are a handful parameters which are especially important: + +* `--min-dist`: Minimum genomic distance from which to detect patterns. For loops, this means the smallest loop size accepted (i.e. distance between the two anchors). +* `--max-dist`: Maximum genomic distance from which to detect patterns. Increasing also increases runtime and memory use. +* `--pearson`: Detection threshold. Decrease to allow a greater number of pattern detected (with potentially more false positives). Setting a very low value may actually reduce the number of detected patterns. This is due to the algorithm which might merge neighbouring patterns. +* `--perc-zero`: Proportion of zero pixels allowed in a window for detection. If you have low coverage, increasing this value may improve results. + +### Example + +To detect all chromosome loops with sizes between 2kb and 200kb using 8 parallel threads: +```bash +chromosight detect --threads 8 --min-dist 20000 --max-dist 200000 hic_data.cool output_prefix +``` + +## Options + +``` + +Pattern exploration and detection + +Explore and detect patterns (loops, borders, centromeres, etc.) in Hi-C contact +maps with pattern matching. + +Usage: + chromosight detect [--kernel-config=FILE] [--pattern=loops] + [--pearson=auto] [--win-size=auto] [--iterations=auto] + [--win-fmt={json,npy}] [--norm={auto,raw,force}] + [--subsample=no] [--inter] [--tsvd] [--smooth-trend] + [--n-mads=5] [--min-dist=0] [--max-dist=auto] + [--no-plotting] [--min-separation=auto] [--dump=DIR] + [--threads=1] [--perc-zero=auto] + [--perc-undetected=auto] <contact_map> <prefix> + chromosight generate-config [--preset loops] [--click contact_map] + [--norm={auto,raw,norm}] [--win-size=auto] [--n-mads=5] + [--threads=1] <prefix> + chromosight quantify [--inter] [--pattern=loops] [--subsample=no] + [--win-fmt=json] [--kernel-config=FILE] [--norm={auto,raw,norm}] + [--threads=1] [--n-mads=5] [--win-size=auto] + [--perc-undetected=auto] [--perc-zero=auto] + [--no-plotting] [--tsvd] <bed2d> <contact_map> <prefix> + chromosight list-kernels [--long] [--mat] [--name=kernel_name] + chromosight test + + detect: + performs pattern detection on a Hi-C contact map via template matching + generate-config: + Generate pre-filled config files to use for detect and quantify. + A config consists of a JSON file describing parameters for the + analysis and path pointing to kernel matrices files. Those matrices + files are tsv files with numeric values as kernel to use for + convolution. + quantify: + Given a list of pairs of positions and a contact map, computes the + correlation coefficients between those positions and the kernel of the + selected pattern. + list-kernels: + Prints information about available kernels. + test: + Download example data and run loop detection on it. + +``` + +## Input + +Input Hi-C contact maps should be in cool format. The cool format is an efficient and compact format for Hi-C data based on HDF5. It is maintained by the Mirny lab and documented here: https://open2c.github.io/cooler/ + +Most other Hi-C data formats (hic, homer, hic-pro), can be converted to cool using [hicexplorer's hicConvertFormat](https://hicexplorer.readthedocs.io/en/latest/content/tools/hicConvertFormat.html) or [hic2cool](https://github.com/4dn-dcic/hic2cool). Bedgraph2 format can be converted directly using cooler with the command `cooler load -f bg2 <chrom.sizes>:<binsize> in.bg2.gz out.cool`. For more informations, see the [cooler documentation](https://cooler.readthedocs.io/en/latest/cli.html#cooler-load) + +For `chromosight quantify`, the bed2d file is a text file with at least 6 tab-separated columns containing pairs of coordinates. The first 6 columns should be `chrom start end chrom start end` and have no header. Alternatively, the output text file generated by `chromosight detect` is also accepted. Instructions to generate a bed2d file from a bed file are given [in the documentation](https://chromosight.readthedocs.io/en/stable/TUTORIAL.html#quantification). + +## Output +Three files are generated by chromosight's `detect` and `quantify` commands. Their filenames are determined by the value of the `<prefix>` argument: + * `prefix.tsv`: List of genomic coordinates, bin ids and correlation scores for the pattern identified + * `prefix.json`: JSON file containing the windows (of the same size as the kernel used) around the patterns from pattern.txt + * `prefix.pdf`: Plot showing the pileup (average) window of all detected patterns. Plot generation can be disabled using the `--no-plotting` option. + +Alternatively, one can set the `--win-fmt=npy` option to dump windows into a npy file instead of JSON. This format can easily be loaded into a 3D array using numpy's `np.load` function. + +> Note: the p-values and q-values provided in prefix.tsv should not be used as a criterion for filtering and are only useful for ranking calls. Their values are obtained from a Pearson correlation test and could be biased due to the dependence between contact values in the window. + +### Contributing + +All contributions are welcome. We use the [numpy standard](https://numpydoc.readthedocs.io/en/latest/format.html) for docstrings when documenting functions. + +The code formatting standard we use is [black](https://github.com/psf/black), with --line-length=79 to follow PEP8 recommendations. We use `nose2` as our testing framework. Ideally, new functions should have associated unit tests, placed in the `tests` folder. + +To test the code, you can run: + +```bash +nose2 -s tests/ +``` + +### FAQ + +Questions from previous users are available in the [github issues](https://github.com/koszullab/chromosight/issues?q=label%3Aquestion). You can open a new issue for your question if it is not already covered. +### Citation +When using Chromosight in you research, please cite the pubication: https://www.nature.com/articles/s41467-020-19562-7 + + +%package -n python3-chromosight +Summary: Detect loops (and other patterns) in Hi-C contact maps. +Provides: python-chromosight +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-chromosight +# Chromosight +<img src="docs/logo/chromosight.gif" alt="animated logo" width="200"/> + +[](https://badge.fury.io/py/chromosight) [](http://bioconda.github.io/recipes/chromosight/README.html) [](https://github.com/koszullab/chromosight/actions/workflows/build.yml) [](https://quay.io/repository/biocontainers/chromosight) [](https://codecov.io/gh/koszullab/chromosight) [](https://chromosight.readthedocs.io) [](https://opensource.org/licenses/GPL-3.0) [](https://lgtm.com/projects/g/koszullab/chromosight/context:python) + +Python package to detect chromatin loops (and other patterns) in Hi-C contact maps. + +* Associated publication: https://www.nature.com/articles/s41467-020-19562-7 +* Documentation and analyses examples: https://chromosight.readthedocs.io +* scripts used for the analysis presented in the article https://github.com/koszullab/chromosight_analyses_scripts + +## Installation + +Stable version with pip: + +```sh +pip3 install --user chromosight +``` +Stable version with conda: +```sh +conda install -c bioconda -c conda-forge chromosight +``` + +or, if you want to get the latest development version: + +``` +pip3 install --user -e git+https://github.com/koszullab/chromosight.git@master#egg=chromosight +``` + +## Usage + +The two main subcommands of `chromosight` are `detect` and `quantify`. For more advanced use, there are two additional subcomands: `generate-config` and `list-kernels`. To get the list and description of those subcommands, you can always run: + +```bash +chromosight --help +``` +Pattern detection is done using the `detect` subcommand. The `quantify` subcommand is used to compute pattern matching scores for a list of 2D coordinates on a Hi-C matrix. The `generate-config` subcommand is used to create a new type of pattern that can then be fed to `detect` using the `--custom-kernel` option. The `list-kernels` command is used to view informations about the available patterns. + +### Get started +To get a first look at a chromosight run, you can run `chromosight test`, which will download a test dataset from the github repository and run `chromosight detect` on it. You can then have a look at the output files generated. + +### Important options + +When running `chromosight detect`, there are a handful parameters which are especially important: + +* `--min-dist`: Minimum genomic distance from which to detect patterns. For loops, this means the smallest loop size accepted (i.e. distance between the two anchors). +* `--max-dist`: Maximum genomic distance from which to detect patterns. Increasing also increases runtime and memory use. +* `--pearson`: Detection threshold. Decrease to allow a greater number of pattern detected (with potentially more false positives). Setting a very low value may actually reduce the number of detected patterns. This is due to the algorithm which might merge neighbouring patterns. +* `--perc-zero`: Proportion of zero pixels allowed in a window for detection. If you have low coverage, increasing this value may improve results. + +### Example + +To detect all chromosome loops with sizes between 2kb and 200kb using 8 parallel threads: +```bash +chromosight detect --threads 8 --min-dist 20000 --max-dist 200000 hic_data.cool output_prefix +``` + +## Options + +``` + +Pattern exploration and detection + +Explore and detect patterns (loops, borders, centromeres, etc.) in Hi-C contact +maps with pattern matching. + +Usage: + chromosight detect [--kernel-config=FILE] [--pattern=loops] + [--pearson=auto] [--win-size=auto] [--iterations=auto] + [--win-fmt={json,npy}] [--norm={auto,raw,force}] + [--subsample=no] [--inter] [--tsvd] [--smooth-trend] + [--n-mads=5] [--min-dist=0] [--max-dist=auto] + [--no-plotting] [--min-separation=auto] [--dump=DIR] + [--threads=1] [--perc-zero=auto] + [--perc-undetected=auto] <contact_map> <prefix> + chromosight generate-config [--preset loops] [--click contact_map] + [--norm={auto,raw,norm}] [--win-size=auto] [--n-mads=5] + [--threads=1] <prefix> + chromosight quantify [--inter] [--pattern=loops] [--subsample=no] + [--win-fmt=json] [--kernel-config=FILE] [--norm={auto,raw,norm}] + [--threads=1] [--n-mads=5] [--win-size=auto] + [--perc-undetected=auto] [--perc-zero=auto] + [--no-plotting] [--tsvd] <bed2d> <contact_map> <prefix> + chromosight list-kernels [--long] [--mat] [--name=kernel_name] + chromosight test + + detect: + performs pattern detection on a Hi-C contact map via template matching + generate-config: + Generate pre-filled config files to use for detect and quantify. + A config consists of a JSON file describing parameters for the + analysis and path pointing to kernel matrices files. Those matrices + files are tsv files with numeric values as kernel to use for + convolution. + quantify: + Given a list of pairs of positions and a contact map, computes the + correlation coefficients between those positions and the kernel of the + selected pattern. + list-kernels: + Prints information about available kernels. + test: + Download example data and run loop detection on it. + +``` + +## Input + +Input Hi-C contact maps should be in cool format. The cool format is an efficient and compact format for Hi-C data based on HDF5. It is maintained by the Mirny lab and documented here: https://open2c.github.io/cooler/ + +Most other Hi-C data formats (hic, homer, hic-pro), can be converted to cool using [hicexplorer's hicConvertFormat](https://hicexplorer.readthedocs.io/en/latest/content/tools/hicConvertFormat.html) or [hic2cool](https://github.com/4dn-dcic/hic2cool). Bedgraph2 format can be converted directly using cooler with the command `cooler load -f bg2 <chrom.sizes>:<binsize> in.bg2.gz out.cool`. For more informations, see the [cooler documentation](https://cooler.readthedocs.io/en/latest/cli.html#cooler-load) + +For `chromosight quantify`, the bed2d file is a text file with at least 6 tab-separated columns containing pairs of coordinates. The first 6 columns should be `chrom start end chrom start end` and have no header. Alternatively, the output text file generated by `chromosight detect` is also accepted. Instructions to generate a bed2d file from a bed file are given [in the documentation](https://chromosight.readthedocs.io/en/stable/TUTORIAL.html#quantification). + +## Output +Three files are generated by chromosight's `detect` and `quantify` commands. Their filenames are determined by the value of the `<prefix>` argument: + * `prefix.tsv`: List of genomic coordinates, bin ids and correlation scores for the pattern identified + * `prefix.json`: JSON file containing the windows (of the same size as the kernel used) around the patterns from pattern.txt + * `prefix.pdf`: Plot showing the pileup (average) window of all detected patterns. Plot generation can be disabled using the `--no-plotting` option. + +Alternatively, one can set the `--win-fmt=npy` option to dump windows into a npy file instead of JSON. This format can easily be loaded into a 3D array using numpy's `np.load` function. + +> Note: the p-values and q-values provided in prefix.tsv should not be used as a criterion for filtering and are only useful for ranking calls. Their values are obtained from a Pearson correlation test and could be biased due to the dependence between contact values in the window. + +### Contributing + +All contributions are welcome. We use the [numpy standard](https://numpydoc.readthedocs.io/en/latest/format.html) for docstrings when documenting functions. + +The code formatting standard we use is [black](https://github.com/psf/black), with --line-length=79 to follow PEP8 recommendations. We use `nose2` as our testing framework. Ideally, new functions should have associated unit tests, placed in the `tests` folder. + +To test the code, you can run: + +```bash +nose2 -s tests/ +``` + +### FAQ + +Questions from previous users are available in the [github issues](https://github.com/koszullab/chromosight/issues?q=label%3Aquestion). You can open a new issue for your question if it is not already covered. +### Citation +When using Chromosight in you research, please cite the pubication: https://www.nature.com/articles/s41467-020-19562-7 + + +%package help +Summary: Development documents and examples for chromosight +Provides: python3-chromosight-doc +%description help +# Chromosight +<img src="docs/logo/chromosight.gif" alt="animated logo" width="200"/> + +[](https://badge.fury.io/py/chromosight) [](http://bioconda.github.io/recipes/chromosight/README.html) [](https://github.com/koszullab/chromosight/actions/workflows/build.yml) [](https://quay.io/repository/biocontainers/chromosight) [](https://codecov.io/gh/koszullab/chromosight) [](https://chromosight.readthedocs.io) [](https://opensource.org/licenses/GPL-3.0) [](https://lgtm.com/projects/g/koszullab/chromosight/context:python) + +Python package to detect chromatin loops (and other patterns) in Hi-C contact maps. + +* Associated publication: https://www.nature.com/articles/s41467-020-19562-7 +* Documentation and analyses examples: https://chromosight.readthedocs.io +* scripts used for the analysis presented in the article https://github.com/koszullab/chromosight_analyses_scripts + +## Installation + +Stable version with pip: + +```sh +pip3 install --user chromosight +``` +Stable version with conda: +```sh +conda install -c bioconda -c conda-forge chromosight +``` + +or, if you want to get the latest development version: + +``` +pip3 install --user -e git+https://github.com/koszullab/chromosight.git@master#egg=chromosight +``` + +## Usage + +The two main subcommands of `chromosight` are `detect` and `quantify`. For more advanced use, there are two additional subcomands: `generate-config` and `list-kernels`. To get the list and description of those subcommands, you can always run: + +```bash +chromosight --help +``` +Pattern detection is done using the `detect` subcommand. The `quantify` subcommand is used to compute pattern matching scores for a list of 2D coordinates on a Hi-C matrix. The `generate-config` subcommand is used to create a new type of pattern that can then be fed to `detect` using the `--custom-kernel` option. The `list-kernels` command is used to view informations about the available patterns. + +### Get started +To get a first look at a chromosight run, you can run `chromosight test`, which will download a test dataset from the github repository and run `chromosight detect` on it. You can then have a look at the output files generated. + +### Important options + +When running `chromosight detect`, there are a handful parameters which are especially important: + +* `--min-dist`: Minimum genomic distance from which to detect patterns. For loops, this means the smallest loop size accepted (i.e. distance between the two anchors). +* `--max-dist`: Maximum genomic distance from which to detect patterns. Increasing also increases runtime and memory use. +* `--pearson`: Detection threshold. Decrease to allow a greater number of pattern detected (with potentially more false positives). Setting a very low value may actually reduce the number of detected patterns. This is due to the algorithm which might merge neighbouring patterns. +* `--perc-zero`: Proportion of zero pixels allowed in a window for detection. If you have low coverage, increasing this value may improve results. + +### Example + +To detect all chromosome loops with sizes between 2kb and 200kb using 8 parallel threads: +```bash +chromosight detect --threads 8 --min-dist 20000 --max-dist 200000 hic_data.cool output_prefix +``` + +## Options + +``` + +Pattern exploration and detection + +Explore and detect patterns (loops, borders, centromeres, etc.) in Hi-C contact +maps with pattern matching. + +Usage: + chromosight detect [--kernel-config=FILE] [--pattern=loops] + [--pearson=auto] [--win-size=auto] [--iterations=auto] + [--win-fmt={json,npy}] [--norm={auto,raw,force}] + [--subsample=no] [--inter] [--tsvd] [--smooth-trend] + [--n-mads=5] [--min-dist=0] [--max-dist=auto] + [--no-plotting] [--min-separation=auto] [--dump=DIR] + [--threads=1] [--perc-zero=auto] + [--perc-undetected=auto] <contact_map> <prefix> + chromosight generate-config [--preset loops] [--click contact_map] + [--norm={auto,raw,norm}] [--win-size=auto] [--n-mads=5] + [--threads=1] <prefix> + chromosight quantify [--inter] [--pattern=loops] [--subsample=no] + [--win-fmt=json] [--kernel-config=FILE] [--norm={auto,raw,norm}] + [--threads=1] [--n-mads=5] [--win-size=auto] + [--perc-undetected=auto] [--perc-zero=auto] + [--no-plotting] [--tsvd] <bed2d> <contact_map> <prefix> + chromosight list-kernels [--long] [--mat] [--name=kernel_name] + chromosight test + + detect: + performs pattern detection on a Hi-C contact map via template matching + generate-config: + Generate pre-filled config files to use for detect and quantify. + A config consists of a JSON file describing parameters for the + analysis and path pointing to kernel matrices files. Those matrices + files are tsv files with numeric values as kernel to use for + convolution. + quantify: + Given a list of pairs of positions and a contact map, computes the + correlation coefficients between those positions and the kernel of the + selected pattern. + list-kernels: + Prints information about available kernels. + test: + Download example data and run loop detection on it. + +``` + +## Input + +Input Hi-C contact maps should be in cool format. The cool format is an efficient and compact format for Hi-C data based on HDF5. It is maintained by the Mirny lab and documented here: https://open2c.github.io/cooler/ + +Most other Hi-C data formats (hic, homer, hic-pro), can be converted to cool using [hicexplorer's hicConvertFormat](https://hicexplorer.readthedocs.io/en/latest/content/tools/hicConvertFormat.html) or [hic2cool](https://github.com/4dn-dcic/hic2cool). Bedgraph2 format can be converted directly using cooler with the command `cooler load -f bg2 <chrom.sizes>:<binsize> in.bg2.gz out.cool`. For more informations, see the [cooler documentation](https://cooler.readthedocs.io/en/latest/cli.html#cooler-load) + +For `chromosight quantify`, the bed2d file is a text file with at least 6 tab-separated columns containing pairs of coordinates. The first 6 columns should be `chrom start end chrom start end` and have no header. Alternatively, the output text file generated by `chromosight detect` is also accepted. Instructions to generate a bed2d file from a bed file are given [in the documentation](https://chromosight.readthedocs.io/en/stable/TUTORIAL.html#quantification). + +## Output +Three files are generated by chromosight's `detect` and `quantify` commands. Their filenames are determined by the value of the `<prefix>` argument: + * `prefix.tsv`: List of genomic coordinates, bin ids and correlation scores for the pattern identified + * `prefix.json`: JSON file containing the windows (of the same size as the kernel used) around the patterns from pattern.txt + * `prefix.pdf`: Plot showing the pileup (average) window of all detected patterns. Plot generation can be disabled using the `--no-plotting` option. + +Alternatively, one can set the `--win-fmt=npy` option to dump windows into a npy file instead of JSON. This format can easily be loaded into a 3D array using numpy's `np.load` function. + +> Note: the p-values and q-values provided in prefix.tsv should not be used as a criterion for filtering and are only useful for ranking calls. Their values are obtained from a Pearson correlation test and could be biased due to the dependence between contact values in the window. + +### Contributing + +All contributions are welcome. We use the [numpy standard](https://numpydoc.readthedocs.io/en/latest/format.html) for docstrings when documenting functions. + +The code formatting standard we use is [black](https://github.com/psf/black), with --line-length=79 to follow PEP8 recommendations. We use `nose2` as our testing framework. Ideally, new functions should have associated unit tests, placed in the `tests` folder. + +To test the code, you can run: + +```bash +nose2 -s tests/ +``` + +### FAQ + +Questions from previous users are available in the [github issues](https://github.com/koszullab/chromosight/issues?q=label%3Aquestion). You can open a new issue for your question if it is not already covered. +### Citation +When using Chromosight in you research, please cite the pubication: https://www.nature.com/articles/s41467-020-19562-7 + + +%prep +%autosetup -n chromosight-1.6.3 + +%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-chromosight -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 1.6.3-1 +- Package Spec generated @@ -0,0 +1 @@ +0a53b62982e00a551ca379489d1914b0 chromosight-1.6.3.tar.gz |