%global _empty_manifest_terminate_build 0 Name: python-treesapp Version: 0.11.4 Release: 1 Summary: TreeSAPP is a functional and taxonomic annotation tool for genomes and metagenomes. License: GPL-3.0 URL: https://github.com/hallamlab/TreeSAPP Source0: https://mirrors.nju.edu.cn/pypi/web/packages/c9/22/768e33057257389a7d4e234e7910768a8ab3a44017e76990be5cca8712a4/treesapp-0.11.4.tar.gz BuildArch: noarch Requires: python3-biopython Requires: python3-ete3 Requires: python3-joblib Requires: python3-numpy Requires: python3-packaging Requires: python3-pyfastx Requires: python3-pygtrie Requires: python3-samsum Requires: python3-scikit-learn Requires: python3-scipy Requires: python3-six Requires: python3-seaborn Requires: python3-tqdm Requires: python3-pytest Requires: python3-pandas Requires: python3-matplotlib Requires: python3-pytest Requires: python3-pytest-cov %description # TreeSAPP: Tree-based Sensitive and Accurate Phylogenetic Profiler ![tests](https://github.com/hallamlab/TreeSAPP/workflows/tests/badge.svg) [![PyPI version](https://badge.fury.io/py/treesapp.svg)](https://badge.fury.io/py/treesapp) [![Anaconda-Server Badge](https://anaconda.org/bioconda/treesapp/badges/version.svg)](https://anaconda.org/bioconda/treesapp) [![Anaconda-Server Badge](https://anaconda.org/bioconda/treesapp/badges/platforms.svg)](https://anaconda.org/bioconda/treesapp) [![Docker Repository on Quay](https://quay.io/repository/hallamlab/treesapp/status "Docker Repository on Quay")](https://quay.io/repository/hallamlab/treesapp) [![Codacy Badge](https://api.codacy.com/project/badge/Grade/b1937000c13040e8bba62f46e954796e)](https://www.codacy.com/gh/hallamlab/TreeSAPP?utm_source=github.com&utm_medium=referral&utm_content=hallamlab/TreeSAPP&utm_campaign=Badge_Grade) [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/treesapp/README.html) [![Python version](https://img.shields.io/pypi/pyversions/treesapp.svg)](https://img.shields.io/pypi/pyversions/) [![codecov](https://codecov.io/gh/hallamlab/TreeSAPP/branch/master/graph/badge.svg)](https://codecov.io/gh/hallamlab/TreeSAPP) [![Anaconda-Server Badge](https://anaconda.org/bioconda/treesapp/badges/downloads.svg)](https://anaconda.org/bioconda/treesapp) ## Overview TreeSAPP is a python package for functional and taxonomic annotation of proteins from genomes and metagenomes using phylogenetic placement. ## Quick start We recommend installing TreeSAPP into its own conda environment with the following command: ```bash conda create -n treesapp_cenv -c bioconda -c conda-forge treesapp conda activate treesapp_cenv ``` To list all the sub-commands run `treesapp`. To test the `assign` workflow, run: ```bash treesapp assign -i TreeSAPP/tests/test_data/marker_test_suite.faa -m prot --trim_align -o assign_test -t McrA,DsrAB ``` To classify sequences in your genome of interest: ```bash treesapp assign -i my.fasta -o ~/path/to/output/directory/ ``` TreeSAPP comes installed with 33 reference packages involved in a variety of biogeochemical and cellular processes. We also have many more reference packages available on our [RefPkgs repository](https://github.com/hallamlab/RefPkgs) and you can view the complete list [here](https://github.com/hallamlab/RefPkgs/wiki/refpkgs). ## Tutorials All of our tutorials are available on the [GitHub wiki](https://github.com/hallamlab/TreeSAPP/wiki) page. Here are some specific tutorial examples: If we do not yet have a reference package for a gene you are interested in, please try [building a new reference package](https://github.com/hallamlab/TreeSAPP/wiki/Building-reference-packages-with-TreeSAPP). Of course, if you run into any problems or would like to collaborate on building many reference packages don't hesitate to email us or create a new issue with an 'enhancement' label. To determine whether the sequences used to build your new reference package are what you think they are, and whether it might unexpectedly annotate homologous sequences, see the [purity tutorial](https://github.com/hallamlab/TreeSAPP/wiki/Testing-the-functional-purity-of-reference-packages). If you are working with a particularly complex reference package, from an orthologous group for example, or have extra phylogenetic information you'd like to include in your classifications, try [annotating extra features](https://github.com/hallamlab/TreeSAPP/wiki/Layering-annotations-onto-classifications) with `treesapp layer`. ## Citation If you found TreeSAPP useful in your work, please cite the following paper: Morgan-Lang, C., McLaughlin, R., Armstrong, Z., Zhang, G., Chan, K., & Hallam, S. J. (2020). [TreeSAPP: The Tree-based Sensitive and Accurate Phylogenetic Profiler](https://doi.org/10.1093/bioinformatics/btaa588). Bioinformatics, 1–8. This was brought to you by the team: - Connor Morgan-Lang ([cmorganl](https://github.com/cmorganl), maintainer) - Ryan McLaughlin ([McGlock](https://github.com/McGlock)) - Grace Zhang ([grace72](https://github.com/gracez72)) - Kevin Chan ([kevinxchan](https://github.com/kevinxchan)) - Zachary Armstrong - Steven J. Hallam ### References If you're feeling extra citation-happy, please consider citing the following works as well: - Eddy, S. R. (1998). Profile hidden Markov models. Bioinformatics (Oxford, England), 14(9), 755–763. - Criscuolo, A., & Gribaldo, S. (2010). BMGE (Block Mapping and Gathering with Entropy): A new software for selection of phylogenetic informative regions from multiple sequence alignments. BMC Evolutionary Biology, 10(1). - Kozlov, A. M., Darriba, D., Flouri, T., Morel, B., & Stamatakis, A. (2019). RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics, 35(21), 4453–4455. - Barbera, P., Kozlov, A. M., Czech, L., Morel, B., & Stamatakis, A. (2018). EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences. Systematic Biology, 0(0), 291658. %package -n python3-treesapp Summary: TreeSAPP is a functional and taxonomic annotation tool for genomes and metagenomes. Provides: python-treesapp BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-treesapp # TreeSAPP: Tree-based Sensitive and Accurate Phylogenetic Profiler ![tests](https://github.com/hallamlab/TreeSAPP/workflows/tests/badge.svg) [![PyPI version](https://badge.fury.io/py/treesapp.svg)](https://badge.fury.io/py/treesapp) [![Anaconda-Server Badge](https://anaconda.org/bioconda/treesapp/badges/version.svg)](https://anaconda.org/bioconda/treesapp) [![Anaconda-Server Badge](https://anaconda.org/bioconda/treesapp/badges/platforms.svg)](https://anaconda.org/bioconda/treesapp) [![Docker Repository on Quay](https://quay.io/repository/hallamlab/treesapp/status "Docker Repository on Quay")](https://quay.io/repository/hallamlab/treesapp) [![Codacy Badge](https://api.codacy.com/project/badge/Grade/b1937000c13040e8bba62f46e954796e)](https://www.codacy.com/gh/hallamlab/TreeSAPP?utm_source=github.com&utm_medium=referral&utm_content=hallamlab/TreeSAPP&utm_campaign=Badge_Grade) [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/treesapp/README.html) [![Python version](https://img.shields.io/pypi/pyversions/treesapp.svg)](https://img.shields.io/pypi/pyversions/) [![codecov](https://codecov.io/gh/hallamlab/TreeSAPP/branch/master/graph/badge.svg)](https://codecov.io/gh/hallamlab/TreeSAPP) [![Anaconda-Server Badge](https://anaconda.org/bioconda/treesapp/badges/downloads.svg)](https://anaconda.org/bioconda/treesapp) ## Overview TreeSAPP is a python package for functional and taxonomic annotation of proteins from genomes and metagenomes using phylogenetic placement. ## Quick start We recommend installing TreeSAPP into its own conda environment with the following command: ```bash conda create -n treesapp_cenv -c bioconda -c conda-forge treesapp conda activate treesapp_cenv ``` To list all the sub-commands run `treesapp`. To test the `assign` workflow, run: ```bash treesapp assign -i TreeSAPP/tests/test_data/marker_test_suite.faa -m prot --trim_align -o assign_test -t McrA,DsrAB ``` To classify sequences in your genome of interest: ```bash treesapp assign -i my.fasta -o ~/path/to/output/directory/ ``` TreeSAPP comes installed with 33 reference packages involved in a variety of biogeochemical and cellular processes. We also have many more reference packages available on our [RefPkgs repository](https://github.com/hallamlab/RefPkgs) and you can view the complete list [here](https://github.com/hallamlab/RefPkgs/wiki/refpkgs). ## Tutorials All of our tutorials are available on the [GitHub wiki](https://github.com/hallamlab/TreeSAPP/wiki) page. Here are some specific tutorial examples: If we do not yet have a reference package for a gene you are interested in, please try [building a new reference package](https://github.com/hallamlab/TreeSAPP/wiki/Building-reference-packages-with-TreeSAPP). Of course, if you run into any problems or would like to collaborate on building many reference packages don't hesitate to email us or create a new issue with an 'enhancement' label. To determine whether the sequences used to build your new reference package are what you think they are, and whether it might unexpectedly annotate homologous sequences, see the [purity tutorial](https://github.com/hallamlab/TreeSAPP/wiki/Testing-the-functional-purity-of-reference-packages). If you are working with a particularly complex reference package, from an orthologous group for example, or have extra phylogenetic information you'd like to include in your classifications, try [annotating extra features](https://github.com/hallamlab/TreeSAPP/wiki/Layering-annotations-onto-classifications) with `treesapp layer`. ## Citation If you found TreeSAPP useful in your work, please cite the following paper: Morgan-Lang, C., McLaughlin, R., Armstrong, Z., Zhang, G., Chan, K., & Hallam, S. J. (2020). [TreeSAPP: The Tree-based Sensitive and Accurate Phylogenetic Profiler](https://doi.org/10.1093/bioinformatics/btaa588). Bioinformatics, 1–8. This was brought to you by the team: - Connor Morgan-Lang ([cmorganl](https://github.com/cmorganl), maintainer) - Ryan McLaughlin ([McGlock](https://github.com/McGlock)) - Grace Zhang ([grace72](https://github.com/gracez72)) - Kevin Chan ([kevinxchan](https://github.com/kevinxchan)) - Zachary Armstrong - Steven J. Hallam ### References If you're feeling extra citation-happy, please consider citing the following works as well: - Eddy, S. R. (1998). Profile hidden Markov models. Bioinformatics (Oxford, England), 14(9), 755–763. - Criscuolo, A., & Gribaldo, S. (2010). BMGE (Block Mapping and Gathering with Entropy): A new software for selection of phylogenetic informative regions from multiple sequence alignments. BMC Evolutionary Biology, 10(1). - Kozlov, A. M., Darriba, D., Flouri, T., Morel, B., & Stamatakis, A. (2019). RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics, 35(21), 4453–4455. - Barbera, P., Kozlov, A. M., Czech, L., Morel, B., & Stamatakis, A. (2018). EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences. Systematic Biology, 0(0), 291658. %package help Summary: Development documents and examples for treesapp Provides: python3-treesapp-doc %description help # TreeSAPP: Tree-based Sensitive and Accurate Phylogenetic Profiler ![tests](https://github.com/hallamlab/TreeSAPP/workflows/tests/badge.svg) [![PyPI version](https://badge.fury.io/py/treesapp.svg)](https://badge.fury.io/py/treesapp) [![Anaconda-Server Badge](https://anaconda.org/bioconda/treesapp/badges/version.svg)](https://anaconda.org/bioconda/treesapp) [![Anaconda-Server Badge](https://anaconda.org/bioconda/treesapp/badges/platforms.svg)](https://anaconda.org/bioconda/treesapp) [![Docker Repository on Quay](https://quay.io/repository/hallamlab/treesapp/status "Docker Repository on Quay")](https://quay.io/repository/hallamlab/treesapp) [![Codacy Badge](https://api.codacy.com/project/badge/Grade/b1937000c13040e8bba62f46e954796e)](https://www.codacy.com/gh/hallamlab/TreeSAPP?utm_source=github.com&utm_medium=referral&utm_content=hallamlab/TreeSAPP&utm_campaign=Badge_Grade) [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/treesapp/README.html) [![Python version](https://img.shields.io/pypi/pyversions/treesapp.svg)](https://img.shields.io/pypi/pyversions/) [![codecov](https://codecov.io/gh/hallamlab/TreeSAPP/branch/master/graph/badge.svg)](https://codecov.io/gh/hallamlab/TreeSAPP) [![Anaconda-Server Badge](https://anaconda.org/bioconda/treesapp/badges/downloads.svg)](https://anaconda.org/bioconda/treesapp) ## Overview TreeSAPP is a python package for functional and taxonomic annotation of proteins from genomes and metagenomes using phylogenetic placement. ## Quick start We recommend installing TreeSAPP into its own conda environment with the following command: ```bash conda create -n treesapp_cenv -c bioconda -c conda-forge treesapp conda activate treesapp_cenv ``` To list all the sub-commands run `treesapp`. To test the `assign` workflow, run: ```bash treesapp assign -i TreeSAPP/tests/test_data/marker_test_suite.faa -m prot --trim_align -o assign_test -t McrA,DsrAB ``` To classify sequences in your genome of interest: ```bash treesapp assign -i my.fasta -o ~/path/to/output/directory/ ``` TreeSAPP comes installed with 33 reference packages involved in a variety of biogeochemical and cellular processes. We also have many more reference packages available on our [RefPkgs repository](https://github.com/hallamlab/RefPkgs) and you can view the complete list [here](https://github.com/hallamlab/RefPkgs/wiki/refpkgs). ## Tutorials All of our tutorials are available on the [GitHub wiki](https://github.com/hallamlab/TreeSAPP/wiki) page. Here are some specific tutorial examples: If we do not yet have a reference package for a gene you are interested in, please try [building a new reference package](https://github.com/hallamlab/TreeSAPP/wiki/Building-reference-packages-with-TreeSAPP). Of course, if you run into any problems or would like to collaborate on building many reference packages don't hesitate to email us or create a new issue with an 'enhancement' label. To determine whether the sequences used to build your new reference package are what you think they are, and whether it might unexpectedly annotate homologous sequences, see the [purity tutorial](https://github.com/hallamlab/TreeSAPP/wiki/Testing-the-functional-purity-of-reference-packages). If you are working with a particularly complex reference package, from an orthologous group for example, or have extra phylogenetic information you'd like to include in your classifications, try [annotating extra features](https://github.com/hallamlab/TreeSAPP/wiki/Layering-annotations-onto-classifications) with `treesapp layer`. ## Citation If you found TreeSAPP useful in your work, please cite the following paper: Morgan-Lang, C., McLaughlin, R., Armstrong, Z., Zhang, G., Chan, K., & Hallam, S. J. (2020). [TreeSAPP: The Tree-based Sensitive and Accurate Phylogenetic Profiler](https://doi.org/10.1093/bioinformatics/btaa588). Bioinformatics, 1–8. This was brought to you by the team: - Connor Morgan-Lang ([cmorganl](https://github.com/cmorganl), maintainer) - Ryan McLaughlin ([McGlock](https://github.com/McGlock)) - Grace Zhang ([grace72](https://github.com/gracez72)) - Kevin Chan ([kevinxchan](https://github.com/kevinxchan)) - Zachary Armstrong - Steven J. Hallam ### References If you're feeling extra citation-happy, please consider citing the following works as well: - Eddy, S. R. (1998). Profile hidden Markov models. Bioinformatics (Oxford, England), 14(9), 755–763. - Criscuolo, A., & Gribaldo, S. (2010). BMGE (Block Mapping and Gathering with Entropy): A new software for selection of phylogenetic informative regions from multiple sequence alignments. BMC Evolutionary Biology, 10(1). - Kozlov, A. M., Darriba, D., Flouri, T., Morel, B., & Stamatakis, A. (2019). RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics, 35(21), 4453–4455. - Barbera, P., Kozlov, A. M., Czech, L., Morel, B., & Stamatakis, A. (2018). EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences. Systematic Biology, 0(0), 291658. %prep %autosetup -n treesapp-0.11.4 %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-treesapp -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue May 30 2023 Python_Bot - 0.11.4-1 - Package Spec generated