Metadata-Version: 2.1
Name: treesapp
Version: 0.9.7
Summary: TreeSAPP is a functional and taxonomic annotation tool for genomes and metagenomes.
Home-page: https://github.com/hallamlab/TreeSAPP
Author: Connor Morgan-Lang
Author-email: c.morganlang@gmail.com
License: GPL-3.0
Description: # TreeSAPP: Tree-based Sensitive and Accurate Phylogenetic Profiler
        
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        ## 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 it's 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/test_data/marker_test_suite.faa -m prot --trim_align -o assign_test -t M0701,M0702,M0705
        ```
        
        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`.
        
        ### Yet to come
        -   [Interpreting `treesapp assign` results]()
        -   [Evaluating classification accuracy]()
        -   [Taxonomically decorating trees for iTOL]()
        -   [Terraform](https://github.com/hallamlab/TreeSAPP/wiki/Running-TreeSAPP-on-Google-Cloud-Platform)
        
        ## 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.
        
Platform: UNKNOWN
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Development Status :: 5 - Production/Stable
Description-Content-Type: text/markdown
Provides-Extra: test
