Metadata-Version: 2.1
Name: gtAI
Version: 1.0.1
Summary: To estimate the tRNA adaptation index (tAI)
Home-page: https://github.com/AliYoussef96/gtAI
Author: Ali Mostafa
Author-email: aliali.mostafa99@gmail.com
License: GPLv3
Description: 
        # Global tRNA Adaptation index (gtAI)
        
        **To estimate the tRNA adaptation index (tAI).**
        
        - For more information about the gtAI: 
        
        - For more information about the tAI: [Mario dos Reis et. al.,](https://academic.oup.com/nar/article/32/17/5036/1333956).
        
        ## Python Support
        
        Python >=3.7 is required.
        
        ## Dependencies
        
        1. Biopython
        
        2. pandas
        
        3. numpy
        
        4. gaft
        
        ## Installation Instructions
        
        **Using pip**
        
        ```python
        pip install gtAI
        ```
        
        ## Contribution Guidelines
        
        Contributions to the software are welcome
        
        For bugs and suggestions, the most effective way is by raising an issue on the github issue tracker. 
        Github allows you to classify your issues so that we know if it is a bug report, feature request or feedback to the authors.
        
        If you wish to contribute some changes to the code then you should submit a [pull request](https://github.com/AliYoussef96/gtAI_pkg/pulls)
        How to create a Pull Request? [documentation on pull requests](https://help.github.com/en/articles/about-pull-requests)
        
        ## Usage
        
        ```python
        from Run_gtAI import gtai_analysis
        
        gtai_analysis(main_fasta, GtRNA, genetic_code_number, size_pop, generation_number=50, bacteria=False)
        ```
        
        Where:
        
        ```python
        
        main_fasta (str): A main fasta file contains genes want to be analyzed (CDS)
        GtRNA (dict): the tRNA genes count
        ref_fasta (str): A reference genes with the highest gene expression in a genome (CDS)
        genetic_code_number (int): default = 1, The Genetic Codes number described by NCBI (https://www.ncbi.nlm.nih.gov/Taxonomy/Utils/wprintgc.cgi)
        size_pop (int): A parameter for the genetic algorithm to identify the population size containing the possible solutions to optimize Sij-values
        generation_number (int): A parameter for the genetic algorithm to identify the generation number
        bacteria (bool): True If the tested organism is prokaryotic or archaea, else equal to False ( default = False )
        
        
        ```
        Returns:
        
        ```python
        df_tai (dataframe): Contains each gene id and its gtAI value 
        final_dict_wi (dict): Contains each codon and its absolute adaptiveness value
        rel_values (dict): Contains each codon and its relative adaptiveness values
        ```
        
        ## Output
        
        ## Example
        
        
        ## API Documentation
        
        You can access the API documentation from here: [gtAI Documentation]()
        
        
        ## Citation
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.7.0
Description-Content-Type: text/markdown
