Metadata-Version: 2.1
Name: dcma
Version: 0.1.2
Summary: Deep Codon Mutation Analyser
Home-page: https://github.com/janjusti/dcma
Author: Jan Justi
Author-email: jan.ma.justi@gmail.com
License: MIT
Description: # Deep Codon Mutation Analyser (DCMA)
        
        DCMA analyses each column of codons within .fasta files, from a target file, generating a report with all possible mutations listed.
        
        ## Installation
        ```bash
        pip install dcma
        ```
        
        ## Examples
        
        - [Simple Execution](examples/example1-simple.md)
        - [Group Execution](examples/example2-group.md)
        
        ## Usage
        ### Command Line
        
        ```bash
        usage: run-dcma [-h] [--reportName REPORTNAME] [--reportPath REPORTPATH]
                        [--searchKP SEARCHKP] [--debug]
                        TARGET REPORTTYPE
        
        Analyse mutation on all nucleotide alignment .fasta files from a target.
        
        positional arguments:
          TARGET                Target .fasta file to be analysed.
          REPORTTYPE            Output report file type.
        
        optional arguments:
          -h, --help            show this help message and exit
          --reportName REPORTNAME
                                Output report custom file name.
          --reportPath REPORTPATH
                                Output report custom file path.
          --searchKP SEARCHKP   Custom keyphrase to detect searchable sequences.
          --debug               Turn debug messages on.
        ```
        
        ### Python
        
        ```python
        import dcma.core as solver
        
        target_path = 'example.fasta'
        report_name = 'myrep'
        report_type = 'all' # 'xls', 'csv' or 'all'
        report_path = 'results-folder' # optional
        
        solver.set_debug_mode(True) # optional
        
        # results[0] -> polarity results dataframe
        # results[1] -> alerts dataframe
        results = solver.run(target_path)
        
        # option 1: export to the current folder
        solver.export(results, report_type, report_name)
        # option 2: export to custom folder
        solver.export(results, report_type, report_name, report_path)
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
