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|
%global _empty_manifest_terminate_build 0
Name: python-SigProfilerSimulator
Version: 1.1.4
Release: 1
Summary: SigProfiler simulator tool
License: UCSD
URL: https://pypi.org/project/SigProfilerSimulator/
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a4/36/6b4e2f2b1cad9582e337792d53f4f7f5210e43559208301c01a1881013dd/SigProfilerSimulator-1.1.4.tar.gz
BuildArch: noarch
Requires: python3-SigProfilerMatrixGenerator
Requires: python3-sigProfilerPlotting
Requires: python3-fastrand
%description
[](https://osf.io/usxjz/wiki/home/) [](https://opensource.org/licenses/BSD-2-Clause) [](https://app.travis-ci.com/AlexandrovLab/SigProfilerSimulator)
# SigProfilerSimulator
SigProfilerSimulator allows realistic simulations of mutational signatures in cancer genomes. The tool can be used to simulate signatures of single point mutations, double point mutations, and insertion/deletions. Further, the tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.
# INTRODUCTION
The purpose of this document is to provide a guide for using the SigProfilerSimulator for simulating mutational signatures in cancer. This tool allows for realistic simulations of single point mutations, double point mutations, and insertions/deletions with the goal of providing a background model for statistical analysis. The simulations are performed in an unbiased fashion, relying on random chance as the main distribution and can be performed across the entire genome or limited to user-provided ranges. This tool currently supports the GRCh37, GRCh38, mm9, and mm10 assemblies, however, additional genomes may be installed. In addition, this tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting. An extensive Wiki page detailing the usage of this tool can be found at https://osf.io/usxjz/wiki/home/.
For users that prefer working in an R environment, a wrapper package is provided and can be found and installed from: https://github.com/AlexandrovLab/SigProfilerSimulatorR
# PREREQUISITES
The framework is written in PYTHON, however, it also requires the following additional software with the given versions (or newer) and access to BASH:
-PYTHON (version 3.4 or newer)
-FASTRAND (Python module: https://github.com/lemire/fastrand/blob/master/README.md )
-SigProfilerMatrixGenerator (Current version: https://github.com/AlexandrovLab/SigProfilerMatrixGenerator )
-Desired reference genome (Follow the installation process on the SigProfilerMatrixGenerator README )
While the code was developed for application on a local computer, access to a cluster with greater computational power may be required for simulating a large number of mutations/samples.
# QUICK START GUIDE
This section will guide you through the minimum steps required to begin simulating mutations:
1. First, install the python package using pip. The R wrapper still requires the python package:
```
pip install SigProfilerSimulator
```
2. Place your vcf files in your desired output folder. It is recommended that you name this folder based on your project's name
3. From within a Python3 session, you can now simulate mutational patterns/signatures as follows:
```
$ python3
>> from SigProfilerSimulator import SigProfilerSimulator as sigSim
>> sigSim.SigProfilerSimulator("BRCA", "/Users/ebergstr/Desktop/BRCA/", "GRCh37", contexts=["96"], exome=None, simulations=100, updating=False, bed_file=None, overlap=False, gender='female', chrom_based=False, seed_file=None, noisePoisson=False, noiseAWGN=0, cushion=100, region=None, vcf=False)
```
The layout of the required parameters are as follows:
SigProfilerSimulator ( project, project_path, genome, contexts)
where project, project_path, and genome must be strings (surrounded by quotation marks, ex: "test"), and contexts is a list of the desired contexts to simulate (ex: contexts=["96", "ID"]) Optional
parameters include:
exome=None: [boolean] Simulates on the exome of the reference genome
simulations=1: [integer] Number of desired iterations per sample. Default is 1 iteration.
updating=False: [boolean] Updated the chromosome with each mutation. Default is FALSE.
bed_file=None: [string path to bed_file] Simulates on custom regions of the genome. Requires the full path to the BED file.
overlap=False: [boolean] Allows overlapping of mutations along the chromosome. Default is FALSE.
gender='female': [string] Simulate male or female genomes. Default is 'female'
chrom_based=False [boolean] Maintains the same catalogs of mutations on a per chromosome basis.
seed_file=None: [string] Path to user defined seeds. One seed is required per processor. Uses a built in file by default
noisePoisson=False: [boolean] Add poisson noise to the simulations. Default is FALSE.
noiseAWGN=0: [Float] Add a noise dependent on a +/- allowance of noise (ex: noiseAWGN=5 allows +/-2.5\% of mutations for each mutation type). Default is 0 noise.
cushion=100: [integer] Allowable cushion when simulating on the exome or targetted panel. Default is 100 base pairs
region=None: [string] Path to targetted region panel for simulated on a user-defined region. Default is whole-genome simulations.
vcf=False [boolean] Outputs simulated samples as vcf files with one file per iteration per sample. By default, the tool outputs all samples from an iteration into a single maf file.
mask=None [string] Path to probability mask file. A mask file format is tab-separated with the following required columns: Chromosome, Start, End, Probability.
Note: Mask parameter does not support exome data where bed_file flag is set to true, and the following header fields are required: Chromosome, Start, End, Probability.
**INPUT FILE FORMAT**
This tool currently supports maf, vcf, simple text file, and ICGC formats. The user must provide variant data adhering to one of these four formats. If the users' files are in vcf format, each sample must be saved as a separate files. For an example input file, please download the simple text file "example.txt" from the following link: [example.txt](https://osf.io/7rdkh/)
**Output File Structure**
The output structure is divided into three folders: input, output, and logs. The input folder contains copies of the user-provided input files. The output folder contains
a DBS, SBS, ID, and simulations folder. The matrices are saved into the appropriate folders, and the simulations are found within a project specific folder under simulations. The logs folder contains the error and log files for the submitted job.
**SUPPORTED GENOMES**
This tool currently supports the following genomes:
GRCh38.p12 [GRCh38] (Genome Reference Consortium Human Reference 37), INSDC
Assembly GCA_000001405.27, Dec 2013. Released July 2014. Last updated January 2018. This genome was downloaded from ENSEMBL database version 93.38.
GRCh37.p13 [GRCh37] (Genome Reference Consortium Human Reference 37), INSDC
Assembly GCA_000001405.14, Feb 2009. Released April 2011. Last updated September 2013. This genome was downloaded from ENSEMBL database version 93.37.
GRCm38.p6 [mm10] (Genome Reference Consortium Mouse Reference 38), INDSDC
Assembly GCA_000001635.8, Jan 2012. Released July 2012. Last updated March 2018. This genome was downloaded from ENSEMBL database version 93.38.
GRCm37 [mm9] (Release 67, NCBIM37), INDSDC Assembly GCA_000001635.18.
Released Jan 2011. Last updated March 2012. This genome was downloaded from ENSEMBL database version release 67.
rn6 (Rnor_6.0) INSDC Assembly GCA_000001895.4, Jul 2014. Released Jun 2015. Last updated Jan 2017.
This genome was downloaded from ENSEMBL database version 96.6.
yeast (Saccharomyces cerevisiae S288C; assembly R64-2-1). Released Nov 2014.
**LOG FILES**
All errors and progress checkpoints are saved into *sigProfilerSimulator_[project]_[genome].err* and *sigProfilerSimulator_[project]_[genome].out*, respectively.
For all errors, please email the error and progress log files to the primary contact under CONTACT INFORMATION.
**CITATION**
Erik N. Bergstrom, Mark Barnes, Iñigo Martincorena, Ludmil B. Alexandrov
bioRxiv 2020.02.13.948422; doi: https://doi.org/10.1101/2020.02.13.948422
https://www.biorxiv.org/content/10.1101/2020.02.13.948422v1
**COPYRIGHT**
Copyright (c) 2020, Erik Bergstrom [Alexandrov Lab] All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
**CONTACT INFORMATION**
Please address any queries or bug reports to Erik Bergstrom at ebergstr@eng.ucsd.edu
%package -n python3-SigProfilerSimulator
Summary: SigProfiler simulator tool
Provides: python-SigProfilerSimulator
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-SigProfilerSimulator
[](https://osf.io/usxjz/wiki/home/) [](https://opensource.org/licenses/BSD-2-Clause) [](https://app.travis-ci.com/AlexandrovLab/SigProfilerSimulator)
# SigProfilerSimulator
SigProfilerSimulator allows realistic simulations of mutational signatures in cancer genomes. The tool can be used to simulate signatures of single point mutations, double point mutations, and insertion/deletions. Further, the tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.
# INTRODUCTION
The purpose of this document is to provide a guide for using the SigProfilerSimulator for simulating mutational signatures in cancer. This tool allows for realistic simulations of single point mutations, double point mutations, and insertions/deletions with the goal of providing a background model for statistical analysis. The simulations are performed in an unbiased fashion, relying on random chance as the main distribution and can be performed across the entire genome or limited to user-provided ranges. This tool currently supports the GRCh37, GRCh38, mm9, and mm10 assemblies, however, additional genomes may be installed. In addition, this tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting. An extensive Wiki page detailing the usage of this tool can be found at https://osf.io/usxjz/wiki/home/.
For users that prefer working in an R environment, a wrapper package is provided and can be found and installed from: https://github.com/AlexandrovLab/SigProfilerSimulatorR
# PREREQUISITES
The framework is written in PYTHON, however, it also requires the following additional software with the given versions (or newer) and access to BASH:
-PYTHON (version 3.4 or newer)
-FASTRAND (Python module: https://github.com/lemire/fastrand/blob/master/README.md )
-SigProfilerMatrixGenerator (Current version: https://github.com/AlexandrovLab/SigProfilerMatrixGenerator )
-Desired reference genome (Follow the installation process on the SigProfilerMatrixGenerator README )
While the code was developed for application on a local computer, access to a cluster with greater computational power may be required for simulating a large number of mutations/samples.
# QUICK START GUIDE
This section will guide you through the minimum steps required to begin simulating mutations:
1. First, install the python package using pip. The R wrapper still requires the python package:
```
pip install SigProfilerSimulator
```
2. Place your vcf files in your desired output folder. It is recommended that you name this folder based on your project's name
3. From within a Python3 session, you can now simulate mutational patterns/signatures as follows:
```
$ python3
>> from SigProfilerSimulator import SigProfilerSimulator as sigSim
>> sigSim.SigProfilerSimulator("BRCA", "/Users/ebergstr/Desktop/BRCA/", "GRCh37", contexts=["96"], exome=None, simulations=100, updating=False, bed_file=None, overlap=False, gender='female', chrom_based=False, seed_file=None, noisePoisson=False, noiseAWGN=0, cushion=100, region=None, vcf=False)
```
The layout of the required parameters are as follows:
SigProfilerSimulator ( project, project_path, genome, contexts)
where project, project_path, and genome must be strings (surrounded by quotation marks, ex: "test"), and contexts is a list of the desired contexts to simulate (ex: contexts=["96", "ID"]) Optional
parameters include:
exome=None: [boolean] Simulates on the exome of the reference genome
simulations=1: [integer] Number of desired iterations per sample. Default is 1 iteration.
updating=False: [boolean] Updated the chromosome with each mutation. Default is FALSE.
bed_file=None: [string path to bed_file] Simulates on custom regions of the genome. Requires the full path to the BED file.
overlap=False: [boolean] Allows overlapping of mutations along the chromosome. Default is FALSE.
gender='female': [string] Simulate male or female genomes. Default is 'female'
chrom_based=False [boolean] Maintains the same catalogs of mutations on a per chromosome basis.
seed_file=None: [string] Path to user defined seeds. One seed is required per processor. Uses a built in file by default
noisePoisson=False: [boolean] Add poisson noise to the simulations. Default is FALSE.
noiseAWGN=0: [Float] Add a noise dependent on a +/- allowance of noise (ex: noiseAWGN=5 allows +/-2.5\% of mutations for each mutation type). Default is 0 noise.
cushion=100: [integer] Allowable cushion when simulating on the exome or targetted panel. Default is 100 base pairs
region=None: [string] Path to targetted region panel for simulated on a user-defined region. Default is whole-genome simulations.
vcf=False [boolean] Outputs simulated samples as vcf files with one file per iteration per sample. By default, the tool outputs all samples from an iteration into a single maf file.
mask=None [string] Path to probability mask file. A mask file format is tab-separated with the following required columns: Chromosome, Start, End, Probability.
Note: Mask parameter does not support exome data where bed_file flag is set to true, and the following header fields are required: Chromosome, Start, End, Probability.
**INPUT FILE FORMAT**
This tool currently supports maf, vcf, simple text file, and ICGC formats. The user must provide variant data adhering to one of these four formats. If the users' files are in vcf format, each sample must be saved as a separate files. For an example input file, please download the simple text file "example.txt" from the following link: [example.txt](https://osf.io/7rdkh/)
**Output File Structure**
The output structure is divided into three folders: input, output, and logs. The input folder contains copies of the user-provided input files. The output folder contains
a DBS, SBS, ID, and simulations folder. The matrices are saved into the appropriate folders, and the simulations are found within a project specific folder under simulations. The logs folder contains the error and log files for the submitted job.
**SUPPORTED GENOMES**
This tool currently supports the following genomes:
GRCh38.p12 [GRCh38] (Genome Reference Consortium Human Reference 37), INSDC
Assembly GCA_000001405.27, Dec 2013. Released July 2014. Last updated January 2018. This genome was downloaded from ENSEMBL database version 93.38.
GRCh37.p13 [GRCh37] (Genome Reference Consortium Human Reference 37), INSDC
Assembly GCA_000001405.14, Feb 2009. Released April 2011. Last updated September 2013. This genome was downloaded from ENSEMBL database version 93.37.
GRCm38.p6 [mm10] (Genome Reference Consortium Mouse Reference 38), INDSDC
Assembly GCA_000001635.8, Jan 2012. Released July 2012. Last updated March 2018. This genome was downloaded from ENSEMBL database version 93.38.
GRCm37 [mm9] (Release 67, NCBIM37), INDSDC Assembly GCA_000001635.18.
Released Jan 2011. Last updated March 2012. This genome was downloaded from ENSEMBL database version release 67.
rn6 (Rnor_6.0) INSDC Assembly GCA_000001895.4, Jul 2014. Released Jun 2015. Last updated Jan 2017.
This genome was downloaded from ENSEMBL database version 96.6.
yeast (Saccharomyces cerevisiae S288C; assembly R64-2-1). Released Nov 2014.
**LOG FILES**
All errors and progress checkpoints are saved into *sigProfilerSimulator_[project]_[genome].err* and *sigProfilerSimulator_[project]_[genome].out*, respectively.
For all errors, please email the error and progress log files to the primary contact under CONTACT INFORMATION.
**CITATION**
Erik N. Bergstrom, Mark Barnes, Iñigo Martincorena, Ludmil B. Alexandrov
bioRxiv 2020.02.13.948422; doi: https://doi.org/10.1101/2020.02.13.948422
https://www.biorxiv.org/content/10.1101/2020.02.13.948422v1
**COPYRIGHT**
Copyright (c) 2020, Erik Bergstrom [Alexandrov Lab] All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
**CONTACT INFORMATION**
Please address any queries or bug reports to Erik Bergstrom at ebergstr@eng.ucsd.edu
%package help
Summary: Development documents and examples for SigProfilerSimulator
Provides: python3-SigProfilerSimulator-doc
%description help
[](https://osf.io/usxjz/wiki/home/) [](https://opensource.org/licenses/BSD-2-Clause) [](https://app.travis-ci.com/AlexandrovLab/SigProfilerSimulator)
# SigProfilerSimulator
SigProfilerSimulator allows realistic simulations of mutational signatures in cancer genomes. The tool can be used to simulate signatures of single point mutations, double point mutations, and insertion/deletions. Further, the tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.
# INTRODUCTION
The purpose of this document is to provide a guide for using the SigProfilerSimulator for simulating mutational signatures in cancer. This tool allows for realistic simulations of single point mutations, double point mutations, and insertions/deletions with the goal of providing a background model for statistical analysis. The simulations are performed in an unbiased fashion, relying on random chance as the main distribution and can be performed across the entire genome or limited to user-provided ranges. This tool currently supports the GRCh37, GRCh38, mm9, and mm10 assemblies, however, additional genomes may be installed. In addition, this tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting. An extensive Wiki page detailing the usage of this tool can be found at https://osf.io/usxjz/wiki/home/.
For users that prefer working in an R environment, a wrapper package is provided and can be found and installed from: https://github.com/AlexandrovLab/SigProfilerSimulatorR
# PREREQUISITES
The framework is written in PYTHON, however, it also requires the following additional software with the given versions (or newer) and access to BASH:
-PYTHON (version 3.4 or newer)
-FASTRAND (Python module: https://github.com/lemire/fastrand/blob/master/README.md )
-SigProfilerMatrixGenerator (Current version: https://github.com/AlexandrovLab/SigProfilerMatrixGenerator )
-Desired reference genome (Follow the installation process on the SigProfilerMatrixGenerator README )
While the code was developed for application on a local computer, access to a cluster with greater computational power may be required for simulating a large number of mutations/samples.
# QUICK START GUIDE
This section will guide you through the minimum steps required to begin simulating mutations:
1. First, install the python package using pip. The R wrapper still requires the python package:
```
pip install SigProfilerSimulator
```
2. Place your vcf files in your desired output folder. It is recommended that you name this folder based on your project's name
3. From within a Python3 session, you can now simulate mutational patterns/signatures as follows:
```
$ python3
>> from SigProfilerSimulator import SigProfilerSimulator as sigSim
>> sigSim.SigProfilerSimulator("BRCA", "/Users/ebergstr/Desktop/BRCA/", "GRCh37", contexts=["96"], exome=None, simulations=100, updating=False, bed_file=None, overlap=False, gender='female', chrom_based=False, seed_file=None, noisePoisson=False, noiseAWGN=0, cushion=100, region=None, vcf=False)
```
The layout of the required parameters are as follows:
SigProfilerSimulator ( project, project_path, genome, contexts)
where project, project_path, and genome must be strings (surrounded by quotation marks, ex: "test"), and contexts is a list of the desired contexts to simulate (ex: contexts=["96", "ID"]) Optional
parameters include:
exome=None: [boolean] Simulates on the exome of the reference genome
simulations=1: [integer] Number of desired iterations per sample. Default is 1 iteration.
updating=False: [boolean] Updated the chromosome with each mutation. Default is FALSE.
bed_file=None: [string path to bed_file] Simulates on custom regions of the genome. Requires the full path to the BED file.
overlap=False: [boolean] Allows overlapping of mutations along the chromosome. Default is FALSE.
gender='female': [string] Simulate male or female genomes. Default is 'female'
chrom_based=False [boolean] Maintains the same catalogs of mutations on a per chromosome basis.
seed_file=None: [string] Path to user defined seeds. One seed is required per processor. Uses a built in file by default
noisePoisson=False: [boolean] Add poisson noise to the simulations. Default is FALSE.
noiseAWGN=0: [Float] Add a noise dependent on a +/- allowance of noise (ex: noiseAWGN=5 allows +/-2.5\% of mutations for each mutation type). Default is 0 noise.
cushion=100: [integer] Allowable cushion when simulating on the exome or targetted panel. Default is 100 base pairs
region=None: [string] Path to targetted region panel for simulated on a user-defined region. Default is whole-genome simulations.
vcf=False [boolean] Outputs simulated samples as vcf files with one file per iteration per sample. By default, the tool outputs all samples from an iteration into a single maf file.
mask=None [string] Path to probability mask file. A mask file format is tab-separated with the following required columns: Chromosome, Start, End, Probability.
Note: Mask parameter does not support exome data where bed_file flag is set to true, and the following header fields are required: Chromosome, Start, End, Probability.
**INPUT FILE FORMAT**
This tool currently supports maf, vcf, simple text file, and ICGC formats. The user must provide variant data adhering to one of these four formats. If the users' files are in vcf format, each sample must be saved as a separate files. For an example input file, please download the simple text file "example.txt" from the following link: [example.txt](https://osf.io/7rdkh/)
**Output File Structure**
The output structure is divided into three folders: input, output, and logs. The input folder contains copies of the user-provided input files. The output folder contains
a DBS, SBS, ID, and simulations folder. The matrices are saved into the appropriate folders, and the simulations are found within a project specific folder under simulations. The logs folder contains the error and log files for the submitted job.
**SUPPORTED GENOMES**
This tool currently supports the following genomes:
GRCh38.p12 [GRCh38] (Genome Reference Consortium Human Reference 37), INSDC
Assembly GCA_000001405.27, Dec 2013. Released July 2014. Last updated January 2018. This genome was downloaded from ENSEMBL database version 93.38.
GRCh37.p13 [GRCh37] (Genome Reference Consortium Human Reference 37), INSDC
Assembly GCA_000001405.14, Feb 2009. Released April 2011. Last updated September 2013. This genome was downloaded from ENSEMBL database version 93.37.
GRCm38.p6 [mm10] (Genome Reference Consortium Mouse Reference 38), INDSDC
Assembly GCA_000001635.8, Jan 2012. Released July 2012. Last updated March 2018. This genome was downloaded from ENSEMBL database version 93.38.
GRCm37 [mm9] (Release 67, NCBIM37), INDSDC Assembly GCA_000001635.18.
Released Jan 2011. Last updated March 2012. This genome was downloaded from ENSEMBL database version release 67.
rn6 (Rnor_6.0) INSDC Assembly GCA_000001895.4, Jul 2014. Released Jun 2015. Last updated Jan 2017.
This genome was downloaded from ENSEMBL database version 96.6.
yeast (Saccharomyces cerevisiae S288C; assembly R64-2-1). Released Nov 2014.
**LOG FILES**
All errors and progress checkpoints are saved into *sigProfilerSimulator_[project]_[genome].err* and *sigProfilerSimulator_[project]_[genome].out*, respectively.
For all errors, please email the error and progress log files to the primary contact under CONTACT INFORMATION.
**CITATION**
Erik N. Bergstrom, Mark Barnes, Iñigo Martincorena, Ludmil B. Alexandrov
bioRxiv 2020.02.13.948422; doi: https://doi.org/10.1101/2020.02.13.948422
https://www.biorxiv.org/content/10.1101/2020.02.13.948422v1
**COPYRIGHT**
Copyright (c) 2020, Erik Bergstrom [Alexandrov Lab] All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
**CONTACT INFORMATION**
Please address any queries or bug reports to Erik Bergstrom at ebergstr@eng.ucsd.edu
%prep
%autosetup -n SigProfilerSimulator-1.1.4
%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-SigProfilerSimulator -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue May 30 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.4-1
- Package Spec generated
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