Metadata-Version: 2.1
Name: fuc
Version: 0.3.2
Summary: Frequently used commands in bioinformatics
Home-page: https://github.com/sbslee/fuc
Author: Seung-been "Steven" Lee
Author-email: sbstevenlee@gmail.com
License: MIT
Description: README
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        .. image:: https://badge.fury.io/py/fuc.svg
            :target: https://badge.fury.io/py/fuc
        
        .. image:: https://readthedocs.org/projects/sbslee-fuc/badge/?version=latest
           :target: https://sbslee-fuc.readthedocs.io/en/latest/?badge=latest
           :alt: Documentation Status
        
        Introduction
        ============
        
        The main goal of the fuc package is to wrap some of the most frequently used commands in the field of bioinformatics into one place.
        
        You can use fuc for both command line interface (CLI) and application programming interface (API) whose documentations are available at `Read the Docs <https://sbslee-fuc.readthedocs.io/en/latest/>`_.
        
        Your contributions (e.g. feature ideas, pull requests) are most welcome.
        
        | Author: Seung-been "Steven" Lee
        | Email: sbstevenlee@gmail.com
        | License: MIT License
        
        Examples
        ========
        
        To merge VCF files with CLI:
        
        .. code-block:: console
        
           $ fuc vfmerge 1.vcf 2.vcf 3.vcf > merged.vcf
        
        To filter a VCF file based on a BED file using API:
        
        .. code:: python3
        
           from fuc import pyvcf
           vf = pyvcf.read_file('original.vcf')
           filtered_vf = vf.filter_bed('targets.bed')
           filtered_vf.to_file('filtered.vcf')
        
        Required Packages
        =================
        
        The following packages are required to run fuc:
        
        .. parsed-literal::
        
           numpy
           pandas
           pyranges
        
        Getting Started
        ===============
        
        There are various ways you can install fuc. The easiest one would be to use pip:
        
        .. code-block:: console
        
           $ pip install fuc
        
        Above will automatically download and install all the dependencies as well.
        
        Alternatively, you can clone the GitHub repository and then install fuc this way:
        
        .. code-block:: console
        
           $ git clone https://github.com/sbslee/fuc
           $ cd fuc
           $ pip install .
        
        Above will also allow you to install a development version that's not available in PyPI.
        
        For getting help on CLI:
        
        .. code-block:: console
        
           $ fuc -h
           usage: fuc [-h] [-v] COMMAND ...
           
           positional arguments:
             COMMAND        name of the command
               bfintxn      [BED] find intersection of two or more BED files
               bfsum        [BED] summarize a BED file
               dfmerge      [TABLE] merge two text files
               dfsum        [TABLE] summarize a text file
               fuccompf     [FUC] compare contents of two files
               fucexist     [FUC] check whether files/dirs exist
               qfcount      [FASTQ] count sequence reads in FASTQ files
               qfsum        [FASTQ] summarize a FASTQ file
               vfmerge      [VCF] merge two or more VCF files
           
           optional arguments:
             -h, --help     show this help message and exit
             -v, --version  show the version number and exit
        
        For getting help on a specific command (e.g. vfmerge):
        
        .. code-block:: console
        
           $ fuc vfmerge -h
        
        Below is the list of submodules available in API:
        
        - **common** : The common submodule is used by other fuc submodules such as pyvcf and pybed. It also provides many day-to-day actions used in the field of bioinformatics.
        - **pybed** : The pybed submodule is designed for working with BED files. It implements ``pybed.BedFrame`` which stores BED data as ``pyranges.PyRanges`` to allow fast computation and easy manipulation.
        - **pyfq** : The pyfq submodule is designed for working with FASTQ files (both zipped and unzipped). It implements ``pyfq.FqFrame`` which stores FASTQ data as ``pandas.DataFrame`` to allow fast computation and easy manipulation.
        - **pysnpeff** : The pysnpeff submodule is designed for parsing VCF annotation data from the SnpEff program. It should be used with ``pyvcf.VcfFrame``.
        - **pyvcf** : The pyvcf submodule is designed for working with VCF files (both zipped and unzipped). It implements ``pyvcf.VcfFrame`` which stores VCF data as ``pandas.DataFrame`` to allow fast computation and easy manipulation.
        - **pyvep** : The pyvep submodule is designed for parsing VCF annotation data from the Ensembl Variant Effect Predictor (VEP). It should be used with ``pyvcf.VcfFrame``.
        
        For getting help on a specific module (e.g. pyvcf):
        
        .. code:: python3
        
           from fuc import pyvcf
           help(pyvcf)
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/x-rst
