Metadata-Version: 1.1
Name: mothur-py
Version: 0.2.4
Summary: Python wrapper for the bioinformatics tool mothur
Home-page: https://github.com/campenr/mothur-py
Author: Richard Campen
Author-email: richard@campen.co
License: Modified BSD License
Description: mothur-py

        =========

        

        Copyright © 2017, Richard Campen. All rights reserved.

        

        See LICENSE.txt for full license conditions.

        

        --------------

        

        Description

        ~~~~~~~~~~~

        

        A python wrapper for the command line version of the bioinformatics tool

        `mothur <https://www.mothur.org/>`__.

        

        Mothur-py was inspired by the

        `ipython-mothurmagic <https://github.com/SchlossLab/ipython-mothurmagic>`__

        module, but with an intention to provide a more general python wrapper

        that would work outside of the IPython/Jupyter notebook environment, as

        well as provide support for mothur's ``current`` keyword functionality.

        

        **Note:** This module has only been tested with mothur v1.39.5 and

        python 3.6 on Windows 10 (64-bit). It should in theory work with other

        versions of mothur, but the older the version the less likely as this

        module relies upon some of the more recent mothur commands/output to

        function properly.

        

        --------------

        

        Installation

        ~~~~~~~~~~~~

        

        To install the latest release version you can just

        ``pip install mothur-py``. To install the most up to date code you

        should download/clone this repository and create a binary distribution

        using ``python setup.py bdist_wheel`` that will create a .whl file in

        the ``dist`` folder. You can then install mothur-py with pip from the

        .whl file using ``pip install <wheel_file_name>``. The advantage of this

        method over just running ``python setup.py install`` is that you can

        easily remove or update the package via pip.

        

        --------------

        

        Basic Usage

        ~~~~~~~~~~~

        

        The use of this module requires that mothur is in the users ``PATH``

        environment variable.

        

        Use of this module revolves around the ``Mothur`` class that catches

        method calls and passes them off to mothur to be run as commands. An

        instance of the ``Mothur`` class needs to be created before running any

        commands:

        

        ::

        

            # create instance of Mothur class

            from mothur_py import Mothur

            m = Mothur()

        

        Commands in mothur can then be executed as methods of the ``Mothur``

        class instance using the same names you would use within the command

        line version of mothur:

        

        ::

        

            # run the mothur help command

            m.help()

        

        Command parameters can either be passed as python native types (i.e.

        strings, integers, floats, booleans, lists) *or* as strings that match

        the format that mothur would expect:

        

        ::

        

            # running make contigs using str input for file parameter, and int for processor paramenter

            m.make.contigs(file='basic_usage.files', processors=2)

        

            # running summary.single, passing calculators as mothur formatted list

            m.summary.single(shared='basic_usage.shared', calc='nseqs-sobs-coverage-shannon-simpson')

        

            # running summary.single, passing calculators as python list also works

            m.summary.single(shared='basic_usage.shared', calc=['nseqs', 'sobs', 'coverage', 'shannon', 'simpson'])

        

        The ``Mothur`` object saves a record of the current directories and

        files and the output files from mothur after executing each command.

        These are stored as dictionary attributes of the ``Mothur`` object and

        can be accessed easily:

        

        ::

        

            # run a command

            m.summary.seqs(fasta='basic_usage.fasta')

        

            # get current output directory

            out_dir = m.current_dirs['output']

        

            # get output file

            with open(m.output_files['summary'][0], 'r') as in_handle:

                in_handle.read()

        

        **NOTE:** Due to the possibility of multiple output files with the same

        extension the output files are saved as lists within the attribute

        dictionaries with the file extension as the key. This issue does not

        occur for current files and dirs so they are stored as the actual

        values, not as lists of the values, with the key being the type of file

        according to mothur (usually the same as the file extension).

        

        **NOTE:** Each successive execution of a mothur command will update the

        current files and dirs, but will completely overwrite the saved output

        files. This is so that you have access to the current files generated

        more than one command ago, but do not get access to output from more

        than one command ago, which would be confusing.

        

        There is also implementation of the ``current`` keyword used in the

        command line version of mothur:

        

        ::

        

            # run the mothur summary.seqs command using the 'current' option

            # NOTE: current is being passed as a string

            m.summary.seqs(fasta='current')

             

            # like the command line version, you don't even need to specify 

            # the 'current' keyword for some commands

            m.summary.seqs() 

        

        Behind the scenes, the ``current`` keyword is enabled by appending the

        users command with the ``get.current()`` command to list the current

        directories and files being used by mothur, parsing of the output to

        extract this information, and prepending future commands with

        ``set.dir()`` and ``set.current()`` to tell mothur what these should be.

        This is necessary as each call to mothur is executed as a separate

        mothur session and therefore mothur can not store this information

        itself.

        

        --------------

        

        Configuration

        ~~~~~~~~~~~~~

        

        The ``Mothur`` class stores configuration options for how mothur is

        executed. These options include ``verbosity`` to control how much output

        there is, ``mothur_seed`` to control the seed used by mothur for random

        number generation, and ``suppress_logfile`` which suppresses the

        creation of the mothur logfile.

        

        When ``verbosity`` is set to ``0`` there is no output printed, ``1``

        prints the normal output as would be seen with command line execution

        (minus the header that contains the mothur version and runtime

        information), and ``2`` displays all output including the commands being

        executed behind the scenes to enable the ``current`` keyword to work.

        The default option is ``0``, with ``1`` being useful when you want to

        see the standard mothur output, and ``2`` being useful for debugging

        purposes.

        

        If ``mothur_seed`` is set to a valid integer then this number will be

        passed to mothur to be used for random number generation. This is

        implemented by adding the ``seed=<your seed here>`` named parameter to

        each mothur command. Not all commands will accept having a seed set. For

        these commands you may need to set the ``mothur_seed`` parameter to

        ``None`` for the execution of that command, e.g.:

        

        ::

        

            m = Mothur(mothur_seed=12345)

        

            # summary.seqs() allows setting the seed so this will run fine

            m.summary.seqs(fasta='current')

        

            # help() does not accept having the seed set so need to alter that value temporarily, otherwise an error will occur

            seed = m.mothur_seed

            m.mothur_seed = None

            m.help()

            m.mothur_seed = seed

        

        The ``supress_logfile`` option is useful when you don't want the log

        files, such as when running in an Jupyter (nee IPython) notebook with

        ``verbosity=1``, in which case you already have a record of mothur's

        output and the mothur logfiles are superfluous.

        

        **Note:** Currently, due to the way that mothur creates the logfiles, a

        logfile will always be created BUT it will be cleaned up upon successful

        execution if ``suppress_logfile=True``. However, if mothur fails to

        successfully execute, i.e. execution hangs or is interrupted, the

        logfile will not be cleaned up. For relevant discussion of this

        behaviour in mothur see

        `here <https://github.com/mothur/mothur/issues/281>`__ and

        `here <https://github.com/mothur/mothur/issues/377>`__.

        

        You can also instantiate the ``Mothur`` object with your desired

        configuration options.

        

        ::

        

            m = Mothur(verbosity=1, mothur_seed=543210, suppress_logfile=True)

        

        --------------

        

        Advanced Usage

        ~~~~~~~~~~~~~~

        

        The current files and current directories for use in mothur are stored

        in dictionary attributes of the ``Mothur`` instance, ``current_files``

        and ``current_dirs`` respectively. These values can be passed to mothur

        commands, e.g:

        

        ::

        

            # passing current fasta file to summary.seqs()

            m.summary.seqs(fasta=m.current_files['fasta'])

               

        

        The ``current`` keyword is actually just a shortcut for this

        functionality so it will always be easier to just pass ``'current'``.

        However, this demonstrates that the parameters of the mothur commands

        can accept any variable as long as it will resolve to something that

        mothur accepts. In the above example, the dictionary value resolves to a

        string that is the path to the ``.fasta`` file. As a better example of

        passing python variables as mothur command parameters, you could perform

        classification of sequences at multiple defined cutoffs as follows:

        

        ::

        

            # iterate over list off possible cutoff values

            for cutoff in [70, 80, 90]:   

                # save outputs to different folders, but keep input the same

                output_dir = 'cutoff_%s' % cutoff

                m.set.dir(output=output_dir, input='.')

                m.classify.seqs(fasta='current', count='current', reference='reference.fasta', taxonomy='referenece.tax',

                cutoff=cutoff)

                

        

        This may be a convoluted example, but it demonstrates the functionality

        well. One note of caution with this approach is that depending on the

        mothur command and the parameter you are changing, you may be

        overwriting your output files as you go. This is the reason for saving

        each output to a different folder in the above example.

        

        You can also instantiate a ``Mothur`` instance with predefined current

        file and directory dictionaries:

        

        ::

        

            m = Mothur(current_files=my_predefined_files_dict, current_dirs=my_predefined_files_dict)

        

        This can be convenient for saving and loading the state of a mothur

        object to/from file as such:

        

        ::

        

            import json

        

            # save state of mothur object, m, to json file

            with open('mothur_object.json', 'w') as out_handle:

                json.dump(vars(m), out_handle)

        

            # can reload mothur object from the json file

            with open('mothur_object.json', 'r') as in_handle:

                m = Mothur(**json.load(in_handle))

        

        You can also modify the contents of these dictionaries in between mothur

        commands. In the previous example where we classified at different

        cutoffs, we could have instead controlled the input and output

        directories in python instead of within mothur:

        

        ::

        

            for cutoff in [70, 80, 90]:   

                # save outputs to different folders, but keep input the same

                m.current_dirs['output'] = 'cutoff_%s' % cutoff

                m.current_dirs['input'] = '.'

        
Keywords: mothur bioinformatics
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Win32 (MS Windows)
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
