Metadata-Version: 2.1
Name: phylopypruner
Version: 0.9.1
Summary: tree-based orthology inference
Home-page: https://gitlab.com/fethalen/phylopypruner
Author: Felix Thalen
Author-email: fe1430th-s@student.lu.se
License: GPL 3
Description: <img src="https://gitlab.com/fethalen/phylopypruner/raw/master/doc/images/ppp_logo.png" alt="ppp_logotype" width="350"/>
        
        ## About
        
        *Orthologs* are genes that are related through a speciation event, while
        *paralogs* are genes that are related through a gene duplication event.
        Accurate identification of orthologs is a prerequisite for phylogenomics, since
        including genes that diverged because of a gene duplication event for species
        tree inference can cause an erroneous inference of speciation nodes, due to
        disparencies between individual gene trees and the species tree. Unfortunately,
        contaminants present in even a single taxon can cause a tree-based orthology
        inference method to erroneuosly infer paralogy and unnecessarily exclude
        sequences.
        
        PhyloPyPruner is a Python package for phylogenetic tree-based orthology
        inference, using the species overlap method. It uses trees and alignments
        inferred from the output of a graph-based orthology inference approach, such
        as [OrthoMCL](https://www.ncbi.nlm.nih.gov/pubmed/12952885),
        [OrthoFinder](https://www.ncbi.nlm.nih.gov/pubmed/26243257) or
        [HaMStR](https://www.ncbi.nlm.nih.gov/pubmed/19586527), in order to obtain sets
        of sequences that are 1:1 orthologous. In addition to algorithms seen in
        pre-existing tree-based tools (for example,
        [PhyloTreePruner](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3825643/),
        [UPhO](https://academic.oup.com/mbe/article/33/8/2117/2578877),
        [Agalma](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3840672/) or
        [Phylogenomic Dataset
        Reconstruction](https://www.ncbi.nlm.nih.gov/pubmed/25158799)), this package
        provides new methods for reducing potential contamination.
        
        ![proteomes2orthologs](https://gitlab.com/fethalen/phylopypruner/raw/master/doc/images/proteomes2orthologs.png)
        
        **Figure 1.** A rough overview of a tree-based orthology inference approach.
        
        ## Quick installation
        
        The easiest way to install PhyloPyPruner is by using the package manager for
        Python, [pip](https://pypi.org/project/pip/):
        
        ```bash
        pip install phylopypruner # install for all users
        pip install --user phylopypruner # install for the current user only
        ```
        
        Once installed, the program is located within `$HOME/.local/bin`. Depending on
        your OS, you might have to add the directory to your `$PATH` to avoid typing
        the entire path. Once in your path, you run the program like this:
        
        ```bash
        phylopypruner
        ```
        
        ## [Documentation](https://gitlab.com/fethalen/phylopypruner/wikis)
        
        1. [About PhyloPyPruner](https://gitlab.com/fethalen/phylopypruner/wikis/about-phylopypruner)
        2. [Tutorial](https://gitlab.com/fethalen/phylopypruner/wikis/tutorial#phylopypruner-tutorial)
        3. [Installation](https://gitlab.com/fethalen/phylopypruner/wikis/installation)
        4. [Input data](https://gitlab.com/fethalen/phylopypruner/wikis/input-data)
        5. [Output files](https://gitlab.com/fethalen/phylopypruner/wikis/output-files)
        6. [Methods](https://gitlab.com/fethalen/phylopypruner/wikis/methods)
        7. [Options](https://gitlab.com/fethalen/phylopypruner/wikis/options)
        
        ## Cite
        
        Our manuscript is still in preparation, it will be posted here once a preprint
        of the article is available.
        
        © [Kocot Lab](https://www.kocotlab.com/) 2019
        
Keywords: orthology inference,orthologs,tree-based,phylogenetics,phylogenomics,orthology
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
