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%global _empty_manifest_terminate_build 0
Name: python-gtdbtk
Version: 2.3.0
Release: 1
Summary: A toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes.
License: GPL3
URL: https://github.com/Ecogenomics/GTDBTk
Source0: https://mirrors.aliyun.com/pypi/web/packages/17/7f/8e724eb5b29d4a3d73d4530e8c9f18296a1f69fde82d634772ed6f0a267a/gtdbtk-2.3.0.tar.gz
BuildArch: noarch
Requires: python3-dendropy
Requires: python3-numpy
Requires: python3-tqdm
Requires: python3-pydantic
%description
# GTDB-Tk
[](https://pypi.python.org/pypi/gtdbtk)
[](https://pepy.tech/project/gtdbtk)
[](https://anaconda.org/bioconda/gtdbtk)
[](https://anaconda.org/bioconda/gtdbtk)
[](https://hub.docker.com/r/ecogenomic/gtdbtk)
[](https://hub.docker.com/r/ecogenomic/gtdbtk)
GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes based
on the Genome Database Taxonomy ([GTDB](https://gtdb.ecogenomic.org/)). It is designed to work with recent advances that
allow hundreds or thousands of metagenome-assembled genomes (MAGs) to be obtained directly from environmental samples.
It can also be applied to isolate and single-cell genomes. The GTDB-Tk is open source and released under the
[GNU General Public License (Version 3)](https://www.gnu.org/licenses/gpl-3.0.en.html).
Notifications about GTDB-Tk releases will be available through the [GTDB Twitter](https://twitter.com/ace_gtdb)
account and the [GTDB Announcements Forum](https://forum.gtdb.ecogenomic.org/c/announcements/10).
Please post questions and issues related to GTDB-Tk on the Issues section of the GitHub repository. Questions
related to the [GTDB](https://gtdb.ecogenomic.org/) can be posted on the [GTDB Forum](https://forum.gtdb.ecogenomic.org/)
or sent to the [GTDB team](https://gtdb.ecogenomic.org/about).
## 🚀 Getting started
Be sure to check the [hardware requirements](https://ecogenomics.github.io/GTDBTk/installing/index.html), then choose your preferred method:
* [Bioconda](https://ecogenomics.github.io/GTDBTk/installing/bioconda.html)
* [Docker](https://ecogenomics.github.io/GTDBTk/installing/docker.html)
* [pip](https://ecogenomics.github.io/GTDBTk/installing/pip.html)
## 📖 Documentation
Documentation for GTDB-Tk can be found [here](https://ecogenomics.github.io/GTDBTk/).
## ✨ New Features
GTDB-Tk v2.3.0+ includes the following new features:
- New functionality ``convert_to_species`` function to convert GTDB genome IDs to GTDB species names
## 📈 Performance
Using ANI screen "can" reduce computation by >50%, although it depends on the set of input genomes. A set of input genomes consisting primarily of new species will not benefit from ANI screen as much as a set of genomes that are largely assigned to GTDB species clusters. In the latter case, the ANI screen will reduce the number of genomes that need to be classified by pplacer which reduces computation time substantially (between 25% and 60% in our testing).
## 📚 References
GTDB-Tk is described in:
* Chaumeil PA, et al. 2022. [GTDB-Tk v2: memory friendly classification with the Genome Taxonomy Database](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btac672/6758240?utm_source=advanceaccess&utm_campaign=bioinformatics&utm_medium=email). <i>Bioinformatics</i>, btac672.
* Chaumeil PA, et al. 2019. [GTDB-Tk: A toolkit to classify genomes with the Genome Taxonomy Database](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btz848/5626182). <i>Bioinformatics</i>, btz848.
The Genome Taxonomy Database (GTDB) is described in:
* Parks, D.H., et al. (2021). [GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy](https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkab776/6370255). <i>Nucleic Acids Research</i>, <b>50</b>: D785–D794.
* Rinke, C, et al. (2021). [A standardized archaeal taxonomy for the Genome Taxonomy Database](https://www.nature.com/articles/s41564-021-00918-8). <i>Nature Microbiology</i>, <b>6</b>: 946–959.
* Parks, D.H., et al. 2020. [A complete domain-to-species taxonomy for Bacteria and Archaea](https://rdcu.be/b3OI7). <i>Nature Biotechnology</i>, https://doi.org/10.1038/s41587-020-0501-8.
* Parks DH, et al. 2018. [A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life](https://www.nature.com/articles/nbt.4229). <i>Nature Biotechnology</i>, http://dx.doi.org/10.1038/nbt.4229.
We strongly encourage you to cite the following 3rd party dependencies:
* Matsen FA, et al. 2010. [pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree](https://www.ncbi.nlm.nih.gov/pubmed/21034504). <i>BMC Bioinformatics</i>, 11:538.
* Jain C, et al. 2019. [High-throughput ANI Analysis of 90K Prokaryotic Genomes Reveals Clear Species Boundaries](https://www.nature.com/articles/s41467-018-07641-9). <i>Nat. Communications</i>, doi: 10.1038/s41467-018-07641-9.
* Hyatt D, et al. 2010. [Prodigal: prokaryotic gene recognition and translation initiation site identification](https://www.ncbi.nlm.nih.gov/pubmed/20211023). <i>BMC Bioinformatics</i>, 11:119. doi: 10.1186/1471-2105-11-119.
* Price MN, et al. 2010. [FastTree 2 - Approximately Maximum-Likelihood Trees for Large Alignments](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2835736/). <i>PLoS One</i>, 5, e9490.
* Eddy SR. 2011. [Accelerated profile HMM searches](https://www.ncbi.nlm.nih.gov/pubmed/22039361). <i>PLOS Comp. Biol.</i>, 7:e1002195.
* Ondov BD, et al. 2016. [Mash: fast genome and metagenome distance estimation using MinHash](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0997-x). <i>Genome Biol</i> 17, 132. doi: 10.1186/s13059-016-0997-x.
## © Copyright
Copyright 2017 Pierre-Alain Chaumeil. See LICENSE for further details.
%package -n python3-gtdbtk
Summary: A toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes.
Provides: python-gtdbtk
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-gtdbtk
# GTDB-Tk
[](https://pypi.python.org/pypi/gtdbtk)
[](https://pepy.tech/project/gtdbtk)
[](https://anaconda.org/bioconda/gtdbtk)
[](https://anaconda.org/bioconda/gtdbtk)
[](https://hub.docker.com/r/ecogenomic/gtdbtk)
[](https://hub.docker.com/r/ecogenomic/gtdbtk)
GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes based
on the Genome Database Taxonomy ([GTDB](https://gtdb.ecogenomic.org/)). It is designed to work with recent advances that
allow hundreds or thousands of metagenome-assembled genomes (MAGs) to be obtained directly from environmental samples.
It can also be applied to isolate and single-cell genomes. The GTDB-Tk is open source and released under the
[GNU General Public License (Version 3)](https://www.gnu.org/licenses/gpl-3.0.en.html).
Notifications about GTDB-Tk releases will be available through the [GTDB Twitter](https://twitter.com/ace_gtdb)
account and the [GTDB Announcements Forum](https://forum.gtdb.ecogenomic.org/c/announcements/10).
Please post questions and issues related to GTDB-Tk on the Issues section of the GitHub repository. Questions
related to the [GTDB](https://gtdb.ecogenomic.org/) can be posted on the [GTDB Forum](https://forum.gtdb.ecogenomic.org/)
or sent to the [GTDB team](https://gtdb.ecogenomic.org/about).
## 🚀 Getting started
Be sure to check the [hardware requirements](https://ecogenomics.github.io/GTDBTk/installing/index.html), then choose your preferred method:
* [Bioconda](https://ecogenomics.github.io/GTDBTk/installing/bioconda.html)
* [Docker](https://ecogenomics.github.io/GTDBTk/installing/docker.html)
* [pip](https://ecogenomics.github.io/GTDBTk/installing/pip.html)
## 📖 Documentation
Documentation for GTDB-Tk can be found [here](https://ecogenomics.github.io/GTDBTk/).
## ✨ New Features
GTDB-Tk v2.3.0+ includes the following new features:
- New functionality ``convert_to_species`` function to convert GTDB genome IDs to GTDB species names
## 📈 Performance
Using ANI screen "can" reduce computation by >50%, although it depends on the set of input genomes. A set of input genomes consisting primarily of new species will not benefit from ANI screen as much as a set of genomes that are largely assigned to GTDB species clusters. In the latter case, the ANI screen will reduce the number of genomes that need to be classified by pplacer which reduces computation time substantially (between 25% and 60% in our testing).
## 📚 References
GTDB-Tk is described in:
* Chaumeil PA, et al. 2022. [GTDB-Tk v2: memory friendly classification with the Genome Taxonomy Database](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btac672/6758240?utm_source=advanceaccess&utm_campaign=bioinformatics&utm_medium=email). <i>Bioinformatics</i>, btac672.
* Chaumeil PA, et al. 2019. [GTDB-Tk: A toolkit to classify genomes with the Genome Taxonomy Database](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btz848/5626182). <i>Bioinformatics</i>, btz848.
The Genome Taxonomy Database (GTDB) is described in:
* Parks, D.H., et al. (2021). [GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy](https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkab776/6370255). <i>Nucleic Acids Research</i>, <b>50</b>: D785–D794.
* Rinke, C, et al. (2021). [A standardized archaeal taxonomy for the Genome Taxonomy Database](https://www.nature.com/articles/s41564-021-00918-8). <i>Nature Microbiology</i>, <b>6</b>: 946–959.
* Parks, D.H., et al. 2020. [A complete domain-to-species taxonomy for Bacteria and Archaea](https://rdcu.be/b3OI7). <i>Nature Biotechnology</i>, https://doi.org/10.1038/s41587-020-0501-8.
* Parks DH, et al. 2018. [A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life](https://www.nature.com/articles/nbt.4229). <i>Nature Biotechnology</i>, http://dx.doi.org/10.1038/nbt.4229.
We strongly encourage you to cite the following 3rd party dependencies:
* Matsen FA, et al. 2010. [pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree](https://www.ncbi.nlm.nih.gov/pubmed/21034504). <i>BMC Bioinformatics</i>, 11:538.
* Jain C, et al. 2019. [High-throughput ANI Analysis of 90K Prokaryotic Genomes Reveals Clear Species Boundaries](https://www.nature.com/articles/s41467-018-07641-9). <i>Nat. Communications</i>, doi: 10.1038/s41467-018-07641-9.
* Hyatt D, et al. 2010. [Prodigal: prokaryotic gene recognition and translation initiation site identification](https://www.ncbi.nlm.nih.gov/pubmed/20211023). <i>BMC Bioinformatics</i>, 11:119. doi: 10.1186/1471-2105-11-119.
* Price MN, et al. 2010. [FastTree 2 - Approximately Maximum-Likelihood Trees for Large Alignments](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2835736/). <i>PLoS One</i>, 5, e9490.
* Eddy SR. 2011. [Accelerated profile HMM searches](https://www.ncbi.nlm.nih.gov/pubmed/22039361). <i>PLOS Comp. Biol.</i>, 7:e1002195.
* Ondov BD, et al. 2016. [Mash: fast genome and metagenome distance estimation using MinHash](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0997-x). <i>Genome Biol</i> 17, 132. doi: 10.1186/s13059-016-0997-x.
## © Copyright
Copyright 2017 Pierre-Alain Chaumeil. See LICENSE for further details.
%package help
Summary: Development documents and examples for gtdbtk
Provides: python3-gtdbtk-doc
%description help
# GTDB-Tk
[](https://pypi.python.org/pypi/gtdbtk)
[](https://pepy.tech/project/gtdbtk)
[](https://anaconda.org/bioconda/gtdbtk)
[](https://anaconda.org/bioconda/gtdbtk)
[](https://hub.docker.com/r/ecogenomic/gtdbtk)
[](https://hub.docker.com/r/ecogenomic/gtdbtk)
GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes based
on the Genome Database Taxonomy ([GTDB](https://gtdb.ecogenomic.org/)). It is designed to work with recent advances that
allow hundreds or thousands of metagenome-assembled genomes (MAGs) to be obtained directly from environmental samples.
It can also be applied to isolate and single-cell genomes. The GTDB-Tk is open source and released under the
[GNU General Public License (Version 3)](https://www.gnu.org/licenses/gpl-3.0.en.html).
Notifications about GTDB-Tk releases will be available through the [GTDB Twitter](https://twitter.com/ace_gtdb)
account and the [GTDB Announcements Forum](https://forum.gtdb.ecogenomic.org/c/announcements/10).
Please post questions and issues related to GTDB-Tk on the Issues section of the GitHub repository. Questions
related to the [GTDB](https://gtdb.ecogenomic.org/) can be posted on the [GTDB Forum](https://forum.gtdb.ecogenomic.org/)
or sent to the [GTDB team](https://gtdb.ecogenomic.org/about).
## 🚀 Getting started
Be sure to check the [hardware requirements](https://ecogenomics.github.io/GTDBTk/installing/index.html), then choose your preferred method:
* [Bioconda](https://ecogenomics.github.io/GTDBTk/installing/bioconda.html)
* [Docker](https://ecogenomics.github.io/GTDBTk/installing/docker.html)
* [pip](https://ecogenomics.github.io/GTDBTk/installing/pip.html)
## 📖 Documentation
Documentation for GTDB-Tk can be found [here](https://ecogenomics.github.io/GTDBTk/).
## ✨ New Features
GTDB-Tk v2.3.0+ includes the following new features:
- New functionality ``convert_to_species`` function to convert GTDB genome IDs to GTDB species names
## 📈 Performance
Using ANI screen "can" reduce computation by >50%, although it depends on the set of input genomes. A set of input genomes consisting primarily of new species will not benefit from ANI screen as much as a set of genomes that are largely assigned to GTDB species clusters. In the latter case, the ANI screen will reduce the number of genomes that need to be classified by pplacer which reduces computation time substantially (between 25% and 60% in our testing).
## 📚 References
GTDB-Tk is described in:
* Chaumeil PA, et al. 2022. [GTDB-Tk v2: memory friendly classification with the Genome Taxonomy Database](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btac672/6758240?utm_source=advanceaccess&utm_campaign=bioinformatics&utm_medium=email). <i>Bioinformatics</i>, btac672.
* Chaumeil PA, et al. 2019. [GTDB-Tk: A toolkit to classify genomes with the Genome Taxonomy Database](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btz848/5626182). <i>Bioinformatics</i>, btz848.
The Genome Taxonomy Database (GTDB) is described in:
* Parks, D.H., et al. (2021). [GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy](https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkab776/6370255). <i>Nucleic Acids Research</i>, <b>50</b>: D785–D794.
* Rinke, C, et al. (2021). [A standardized archaeal taxonomy for the Genome Taxonomy Database](https://www.nature.com/articles/s41564-021-00918-8). <i>Nature Microbiology</i>, <b>6</b>: 946–959.
* Parks, D.H., et al. 2020. [A complete domain-to-species taxonomy for Bacteria and Archaea](https://rdcu.be/b3OI7). <i>Nature Biotechnology</i>, https://doi.org/10.1038/s41587-020-0501-8.
* Parks DH, et al. 2018. [A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life](https://www.nature.com/articles/nbt.4229). <i>Nature Biotechnology</i>, http://dx.doi.org/10.1038/nbt.4229.
We strongly encourage you to cite the following 3rd party dependencies:
* Matsen FA, et al. 2010. [pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree](https://www.ncbi.nlm.nih.gov/pubmed/21034504). <i>BMC Bioinformatics</i>, 11:538.
* Jain C, et al. 2019. [High-throughput ANI Analysis of 90K Prokaryotic Genomes Reveals Clear Species Boundaries](https://www.nature.com/articles/s41467-018-07641-9). <i>Nat. Communications</i>, doi: 10.1038/s41467-018-07641-9.
* Hyatt D, et al. 2010. [Prodigal: prokaryotic gene recognition and translation initiation site identification](https://www.ncbi.nlm.nih.gov/pubmed/20211023). <i>BMC Bioinformatics</i>, 11:119. doi: 10.1186/1471-2105-11-119.
* Price MN, et al. 2010. [FastTree 2 - Approximately Maximum-Likelihood Trees for Large Alignments](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2835736/). <i>PLoS One</i>, 5, e9490.
* Eddy SR. 2011. [Accelerated profile HMM searches](https://www.ncbi.nlm.nih.gov/pubmed/22039361). <i>PLOS Comp. Biol.</i>, 7:e1002195.
* Ondov BD, et al. 2016. [Mash: fast genome and metagenome distance estimation using MinHash](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0997-x). <i>Genome Biol</i> 17, 132. doi: 10.1186/s13059-016-0997-x.
## © Copyright
Copyright 2017 Pierre-Alain Chaumeil. See LICENSE for further details.
%prep
%autosetup -n gtdbtk-2.3.0
%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-gtdbtk -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 2.3.0-1
- Package Spec generated
|
