{
    "info": {
        "author": "Bj\u00f6rn Johansson",
        "author_email": "bjorn_johansson@bio.uminho.pt",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Console",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Education",
            "Topic :: Scientific/Engineering :: Bio-Informatics"
        ],
        "description": "# ![icon](https://raw.githubusercontent.com/bjornFJohansson/pydna/release/docs/pics/pydna.resized.png) pydna\n\nPlanning genetic constructs with many parts and assembly steps, such as recombinant\nmetabolic pathways are often difficult to properly document.\n\nThe Pydna python package provide a human-readable formal description of cloning and assembly \nstrategies in Python which also allows for simulation and verification of cloning strategies.\nPydna can be though of as executable documentation for molecular biology. \n\nPydna provides simulation of:\n\n- Restriction digestion\n- Ligation\n- PCR\n- Primer design\n- Gibson assembly\n- Golden gate assembly\n- Homologous recombination\n- Gel electrophoresis of DNA with generation of gel images\n\nVirtually any sub-cloning experiment can be described in pydna, and its execution yield\nthe sequence of the of intermediate and final resulting DNA molecule(s). \nA cloning strategy expressed in pydna is *complete*, *unambiguous* and can be made *stable*. \nPydna has been designed to be understandable for biologists with only some basic understanding of Python.\n\nPydna can formalize planning and sharing of cloning strategies and is especially useful for complex or combinatorial\nDNA molecule constructions.\n\nLook at some assembly strategies made in the Jupyter notebook\nformat [here](http://nbviewer.ipython.org/github/BjornFJohansson/ypk-xylose-pathways/blob/release/index.ipynb).\n\nThere is an open access paper in BMC Bioinformatics describing pydna:\n\n[![abstr](https://raw.githubusercontent.com/bjornFJohansson/pydna/release/docs/pics/BMC_resized.png)](http://www.biomedcentral.com/1471-2105/16/142/abstract)\n\nPlease reference the above paper when using pydna.\n\n## Usage\n\nMost pydna functionality is implemented as methods for the double stranded DNA sequence record \nclasses Dseq and Dseqrecord, which are subclasses of the [Biopython](http://biopython.org/wiki/Main_Page) [Seq](http://biopython.org/wiki/Seq) and [SeqRecord](http://biopython.org/wiki/SeqRecord) classes.\n\nThese classes make cut and paste cloning and PCR very simple:\n\n    >>> from pydna.dseq import Dseq\n    >>> seq = Dseq(\"GGATCCAAA\",\"TTTGGATCC\",ovhg=0)\n    >>> seq\n    Dseq(-9)\n    GGATCCAAA\n    CCTAGGTTT\n    >>> from Bio.Restriction import BamHI\n    >>> a,b = seq.cut(BamHI)\n    >>> a\n    Dseq(-5)\n    G\n    CCTAG\n    >>> b\n    Dseq(-8)\n    GATCCAAA\n        GTTT\n    >>> a+b\n    Dseq(-9)\n    GGATCCAAA\n    CCTAGGTTT\n    >>> b+a\n    Dseq(-13)\n    GATCCAAAG\n        GTTTCCTAG\n    >>> b+a+b\n    Dseq(-17)\n    GATCCAAAGGATCCAAA\n        GTTTCCTAGGTTT\n    >>> b+a+a\n    Traceback (most recent call last):\n      File \"<stdin>\", line 1, in <module>\n      File \"/usr/local/lib/python2.7/dist-packages/pydna/dsdna.py\", line 217, in __add__\n        raise TypeError(\"sticky ends not compatible!\")\n    TypeError: sticky ends not compatible!\n    >>>\n\nAs the example above shows, pydna keeps track of sticky ends.\n\nNotably, homologous recombination and Gibson assembly between linear DNA fragments \ncan be easily simulated without any additional information besides the primary sequence of the fragments.\n\nGel electrophoresis of DNA fragments can be simulated using the included gel module \nby [Bruno Silva](https://github.com/bruno2git):\n\n![alt text](https://raw.githubusercontent.com/bjornFJohansson/pydna/release/docs/pics/gel.png \"simulated agarose gel\")\n\nLook at an example notebook with a gel simulation [here](http://nbviewer.jupyter.org/github/BjornFJohansson/pydna/blob/release/scripts/gel_inline_ex.ipynb).\n\nPydna can be very compact. The nine lines of Python below, simulates the construction of a recombinant plasmid. \nDNA sequences are downloaded from Genbank by accession numbers that are guaranteed to be stable over time.\n\n    from pydna.genbank import Genbank\n    gb = Genbank(\"myself@email.com\") # Tell Genbank who you are!\n    gene = gb.nucleotide(\"X06997\") # Kluyveromyces lactis LAC12 gene for lactose permease.\n    from pydna.parsers import parse_primers\n    primer_f,primer_r = parse_primers(''' >760_KlLAC12_rv (20-mer)\n                                          ttaaacagattctgcctctg\n\n                                          >759_KlLAC12_fw (19-mer)\n                                          aaatggcagatcattcgag ''')\n    from pydna.amplify import pcr\n    pcr_prod = pcr(primer_f,primer_r, gene)\n    vector = gb.nucleotide(\"AJ001614\") # pCAPs cloning vector\n    from Bio.Restriction import EcoRV\n    lin_vector = vector.linearize(EcoRV)\n    rec_vec =  ( lin_vector + pcr_prod ).looped()\n\nPydna can automate the simulation of [sub cloning](http://en.wikipedia.org/wiki/Subcloning) experiments using\npython. This is helpful to generate examples for teaching purposes. \n\nRead the [documentation](http://pydna.readthedocs.io/index.html) or the [cookbook](https://www.dropbox.com/sh/4re9a0wk03m95z4/AABpu4zwq4IuKUvK0Iy9Io0Fa?dl=0) with example files\nfor further information.\n\nPlease post a message in the [google group](https://groups.google.com/d/forum/pydna)\nfor pydna if you have problems, questions or comments.\n\nFeedback is very welcome!\n## Who is using pydna?\n\n[An Automated Protein Synthesis Pipeline with Transcriptic and Snakemake](http://blog.booleanbiotech.com/transcriptic_protein_synthesis_pipeline.html)\n\n[Pyviko: an automated Python tool to design gene knockouts in complex viruses with overlapping genes](https://www.ncbi.nlm.nih.gov/pubmed/28061810)\n\n## Documentation\n\nDocumentation is built using [Sphinx](http://www.sphinx-doc.org/) from [docstrings](https://www.python.org/dev/peps/pep-0257/)\nin the code and displayed at readthedocs [![Documentation Status](https://readthedocs.org/projects/pydna/badge/?version=latest)](http://pydna.readthedocs.io/?badge=latest)\n\nThe [numpy](www.numpy.org) [docstring format](https://github.com/numpy/numpy/blob/release/doc/HOWTO_DOCUMENT.rst.txt) is used.\n\n## Installation using conda on Anaconda\n\nThe absolutely best way of installing and using pydna is to use the \nfree [Anaconda](https://store.continuum.io/cshop/anaconda) or [Miniconda](http://conda.pydata.org/miniconda.html) python distributions.\n\nAnaconda is a large download (about 400 Mb) while Miniconda is about 40-50 Mb. \n\nOnce Anaconda (or Miniconda) is installed, the conda package manager can be used to install pydna.\nPydna and its dependencies are available from the [BjornFJohansson](https://anaconda.org/bjornfjohansson) package channel at \n[Anaconda.org](https://anaconda.org).\n\nThe first step is to add the channel by typing the command below followed by return:\n\n    conda config --append channels BjornFJohansson\n\nThen pydna can be installed by typing the command below followed by return:\n\n    conda install pydna\n\nThis works on Windows, MacOSX and Linux, and installs all necessary and optional dependencies automatically (see below).\n\n## Installation using pip\n\nThe second best way of installing pydna is with pip, the\nofficially [recommended](http://python-packaging-user-guide.readthedocs.org/en/latest) tool.\n\nPip is included in recent Python versions.\n\nPip installs the minimal installation requirements automatically, but not the optional requirements (see below). \nThis will probably not work directly on windows, as biopython is not directly installable. \n\n### Linux:\n\n    bjorn@bjorn-UL30A:~/pydna$ sudo pip install pydna\n\n### Windows:\n\nYou should be able to pip install pydna from the Windows terminal as biopython now can be installed with pip as well.\n\n    C:\\> pip install pydna\n\nBy default python and pip are not on the PATH. You can re-install Python and select this option, or give \nthe full path for pip. Try something like this, depending on where your copy of Python is installed:\n\n    C:\\Python37\\Scripts\\pip install pydna\n\n## Installation from Source\n\nIf you install from source, you need to install all dependencies separately (listed above). \nDownload one of the source installers from the pypi site or from Github and extract the file. \nOpen the pydna source code directory (containing the setup.py file) in\nterminal and type:\n\n    python setup.py install\n\n## Source Code\n\nPydna is developed on [Github](https://github.com/BjornFJohansson/pydna).\n\n## Minimal installation requirements\n\nPydna is currently developed on and for Python 3.6 or 3.7. Pydna versions before 1.0.0 were compatible with python 2.7 only. \nThe list below is the minimal requirements for installing pydna. Biopython has c-extensions, but the other modules are pure python. \n\n- [Python 3.6 or 3.7](http://www.python.org)\n- [biopython >= 1.65](http://pypi.python.org/pypi/biopython)\n- [networkx >= 1.8.1](http://pypi.python.org/pypi/networkx)\n- [pyparsing >= 2.1.10](https://pypi.python.org/pypi/pyparsing)\n- [appdirs >=1.3.0](https://pypi.python.org/pypi/appdirs)\n- [prettytable>=0.7.2](https://pypi.python.org/pypi/PrettyTable)\n\n## Optional Requirements\nPydna has been designed to be used from the Jupyter notebook. If [IPython](https://ipython.org/) \nand [Jupyter](http://jupyter.org/) are installed, importing ipython notebooks as modules among are \nsupported among other things.\n\nIf the modules listed below are installed, gel simulation functionality is available.\n\n- [numpy](http://www.numpy.org)\n- [scipy](https://www.scipy.org)\n- [matplotlib](http://matplotlib.org)\n- [mpldatacursor](https://pypi.python.org/pypi/mpldatacursor)\n- [pint >= 0.7.2](https://pypi.python.org/pypi/pint)\n\nThe pydna conda package installs the optional requirements listed above as well as:\n\n- [ipython](https://pypi.python.org/pypi/ipython)\n- [jupyter](https://pypi.python.org/pypi/jupyter)\n\n## Requirements for running tests\n\n- [pytest>=3.0.3](https://pypi.python.org/pypi/pytest)\n\n## Requirements for analyzing code coverage\n\n- [python-coveralls >= 2.9.0](https://pypi.python.org/pypi/python-coveralls)\n- [coverage >= 3.7.1](https://pypi.python.org/pypi/coverage)\n- [pytest-cov >= 2.3.1](https://pypi.python.org/pypi/pytest-cov)\n\n## Automatic testing\n\nThe test suit is run automatically after each commit on:\n\n- Ubuntu 14.04 using Codeship\n- OSX-64 using TravisCI\n- Windows using AppveyorCI\n\nSee the badges at the top of this page.\n\n## Automatic builds\n\n[Conda](http://conda.pydata.org/docs/intro.html) packages are built on Codeship(Linux), TravisCI(MacOS) and AppveyorCI(Windows). \nSource setuptools packages and wheels are built on Linux for all systems.\nBinary setuptools packages are built for Windows and MacOSX.\n\n- Conda packages [![Anaconda-Server Badge0](https://anaconda.org/bjornfjohansson/pydna/badges/version.svg)](https://anaconda.org/bjornfjohansson/pydna)\n- Setuptools packages\n\nBuilds are controlled by Git tags. Tags like 1.0.2a4 are considered test builds and are uploaded to \n[testpypi](https://testpypi.python.org/pypi?:action=display&name=pydna) and to Anaconda.org with a \"test\" label. \nThese are only meant to test the finished packages and are not meant to be used.\n\nTags like 1.0.3 are considered final builds and are built and uploaded to [Anaconda.org](https://anaconda.org/BjornFJohansson/pydna) under the \"main\" label \nand to the regular [pypi](https://pypi.python.org/pypi/pydna) server.\n\n## Changelog\nSee the [change log](docs/CHANGELOG.md) for recent changes.\n\n|                                |                                                                                                                                                                                       |\n|--------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Stars                          | [![GitHub stars](https://img.shields.io/github/stars/BjornFJohansson/pydna.svg)](https://github.com/BjornFJohansson/pydna/stargazers)                                                 |\n| Documentation                  | [![Documentation Status](https://readthedocs.org/projects/pydna/badge/?version=latest)](http://pydna.readthedocs.io/?badge=latest)                                                    |\n| Issues                         | [![GitHub issues](https://img.shields.io/github/issues/BjornFJohansson/pydna.svg)](https://github.com/BjornFJohansson/pydna/issues)                                                   |\n| Test coverage                  | [![codecov](https://codecov.io/gh/BjornFJohansson/pydna/branch/release/graph/badge.svg)](https://codecov.io/gh/BjornFJohansson/pydna)                                                  |\n| Conda package for platorms     | [![Anaconda-Server Badge](https://anaconda.org/bjornfjohansson/pydna/badges/platforms.svg)](https://anaconda.org/bjornfjohansson/pydna)                                               |\n| Test and build on Linux        | [![Codeship Status for BjornFJohansson/pydna](https://app.codeship.com/projects/de24d6c0-f3a7-0135-0950-76dd9f7b94ca/status)](https://app.codeship.com/projects/272770) |\n| Test and build on  MacOSX      | [![icon1](https://travis-ci.org/BjornFJohansson/pydna.svg)](https://travis-ci.org/BjornFJohansson/pydna)                                                                              |\n| Test and build on  Windows     | [![icon2](https://ci.appveyor.com/api/projects/status/qdtk9biw5o0cae7u?svg=true)](https://ci.appveyor.com/project/BjornFJohansson/pydna)                                              |\n| Setuptools package             | [![PyPI version](https://badge.fury.io/py/pydna.svg)](https://badge.fury.io/py/pydna)                                                                                                 |\n| Conda package                  | [![Anaconda-Server Badge0](https://anaconda.org/bjornfjohansson/pydna/badges/version.svg)](https://anaconda.org/bjornfjohansson/pydna)                                                |\n| Software license               | [![Anaconda-Server Badge2](https://anaconda.org/bjornfjohansson/pydna/badges/license.svg)](https://anaconda.org/bjornfjohansson/pydna)                                                |\n\n\n",
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