Metadata-Version: 2.1
Name: pyoinformatics
Version: 0.1.6
Summary: A simple bioinformatics package
Home-page: https://github.com/Wytamma/pyoinformatics
Author: Wytamma Wirth
Author-email: wytamma.wirth@me.com
License: UNKNOWN
Description: # pyoinformatics 🐍
        [![CI/CD](https://github.com/Wytamma/pyoinformatics/workflows/CI/CD/badge.svg)](https://github.com/Wytamma/pyoinformatics/actions?query=workflow%3ACI%2FCD)
        [![codecov](https://codecov.io/gh/Wytamma/pyoinformatics/branch/master/graph/badge.svg)](https://codecov.io/gh/Wytamma/pyoinformatics)
        [![image](https://img.shields.io/github/license/wytamma/pyoinformatics.svg)](https://img.shields.io/github/license/wytamma/pyoinformatics)
        [![black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://img.shields.io/badge/code%20style-black-000000.svg)
        [![PyPI](https://img.shields.io/pypi/v/pyoinformatics)](https://pypi.org/project/pyoinformatics/)
        
        
        `pip install pyoinformatics`
        
        ## Examples 
        
        ### Find the reverse complement of all the sequences in a file:
        ```python
        import pyoinformatics as pyo
        
        with open('out.fasta', 'w') as f:
          for seq in pyo.read_fasta('in.fasta'):
            f.writelines(seq.reverse_complement().to_fasta())
        ```
        
        ### Count the number of occurrences of 'ATG' in seq object
        ```python
        seq.count('ATG')
        ```
        
        ### Count the number of occurrences of 'ATG' in seq object that differ by <= 1 base.
        ```python
        seq.count('ATG', 1)
        ```
        
        ### Find the average position of all occurrences of 'ATG' in a fasta file
        ```python
        from statistics import mean
        for seq in pyo.read_fasta('in.fasta'):
          print(mean(seq.find('ATG')))
        ```
        
        ### Find the number of occurrences of 'ATG' or 'AAG' in seq object
        ```python
        len(seq1.find('A[AT]G'))
        ```
        
        ### ASCI plot the relative nt counts for all the sequences in a file
        ```python
        for seq in pyo.read_fasta('in.fasta'):
          counts = seq.counts
          print(f">{seq.id}")
          for nt in sorted(counts.keys()):
            bar = int((counts[nt]/len(seq))*100)
            print(f"{nt}: {'◊' * bar}")
        
        >HSBGPG Human gene for bone gla protein (BGP)
        A: ◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊
        C: ◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊
        G: ◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊
        T: ◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊
        >HSGLTH1 Human theta 1-globin gene
        A: ◊◊◊◊◊◊◊◊◊◊◊◊◊◊
        C: ◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊
        G: ◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊
        T: ◊◊◊◊◊◊◊◊◊◊◊◊◊◊◊
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
