Metadata-Version: 1.1
Name: pyfaidx
Version: 0.3.6
Summary: pyfaidx: efficient pythonic random access to fasta subsequences
Home-page: http://mattshirley.com
Author: Matthew Shirley
Author-email: mdshw5@gmail.com
License: MIT
Description: |Travis| |PyPI| |Landscape| |Coveralls|
        
        Description
        -----------
        
        Samtools provides a function "faidx" (FAsta InDeX), which creates a
        small flat index file ".fai" allowing for fast random access to any
        subsequence in the indexed FASTA file, while loading a minimal amount of the
        file in to memory. This python module implements pure Python classes for
        indexing, retrieval, and in-place modification of FASTA files.
        
        A `manuscript <https://www.authorea.com/users/3882/articles/14770/_show_article>`_ is
        currently under preparation.
        
        Installation
        ------------
        
        This package is tested under Linux, MacOS, and Windows using Python 3.2-3.4, 2.7, 2.6, and pypy.
        
        ::
        
            pip install pyfaidx
        
            or
        
            python setup.py install
        
        Usage
        -----
        
        .. _benchmark: http://www.biostars.org/p/93364/#93390
        
        .. code:: python
        
            >>> from pyfaidx import Fasta
            >>> genes = Fasta('tests/data/genes.fasta')
            >>> genes
            Fasta("tests/data/genes.fasta")  # set strict_bounds=True for bounds checking
        
        Acts like a dictionary.
        
        .. code:: python
        
            >>> genes.keys() ('AB821309.1', 'KF435150.1', 'KF435149.1', 'NR_104216.1', 'NR_104215.1', 'NR_104212.1', 'NM_001282545.1', 'NM_001282543.1', 'NM_000465.3', 'NM_001282549.1', 'NM_001282548.1', 'XM_005249645.1', 'XM_005249644.1', 'XM_005249643.1', 'XM_005249642.1', 'XM_005265508.1', 'XM_005265507.1', 'XR_241081.1', 'XR_241080.1', 'XR_241079.1')
        
            >>> genes['NM_001282543.1'][200:230]
            >NM_001282543.1:201-230
            CTCGTTCCGCGCCCGCCATGGAACCGGATG
        
            >>> genes['NM_001282543.1'][200:230].seq
            'CTCGTTCCGCGCCCGCCATGGAACCGGATG'
        
            >>> genes['NM_001282543.1'][200:230].name
            'NM_001282543.1'
        
            >>> genes['NM_001282543.1'][200:230].start
            201
        
            >>> genes['NM_001282543.1'][200:230].end
            230
        
            >>> genes['NM_001282543.1'][200:230].longname
            'NM_001282543.1:201-230'
        
            >>> len(genes['NM_001282543.1'])
            5466
        
        Indexes like a list:
        
        .. code:: python
        
            >>> genes[0][:50]
            >AB821309.1:1-50
            ATGGTCAGCTGGGGTCGTTTCATCTGCCTGGTCGTGGTCACCATGGCAAC
        
        Slices just like a string:
        
        .. code:: python
        
            >>> genes['NM_001282543.1'][200:230][:10]
            >NM_001282543.1:201-210
            CTCGTTCCGC
        
            >>> genes['NM_001282543.1'][200:230][::-1]
            >NM_001282543.1:230-201
            GTAGGCCAAGGTACCGCCCGCGCCTTGCTC
        
            >>> genes['NM_001282543.1'][200:230][::3]
            >NM_001282543.1:201-230
            CGCCCCTACA
        
            >>> genes['NM_001282543.1'][:]
            >NM_001282543.1:1-5466
            CCCCGCCCCT........
        
        - Start and end coordinates are 0-based, just like Python.
        
        Sequence can be buffered in memory using a read-ahead buffer
        for fast sequential access:
        
        .. code:: python
        
            >>> from timeit import timeit
            >>> fetch = "genes['NM_001282543.1'][200:230]"
            >>> read_ahead = "import pyfaidx; genes = pyfaidx.Fasta('tests/data/genes.fasta', read_ahead=10000)"
            >>> no_read_ahead = "import pyfaidx; genes = pyfaidx.Fasta('tests/data/genes.fasta')"
            >>> string_slicing = "genes = {}; genes['NM_001282543.1'] = 'N'*10000"
        
            >>> timeit(fetch, no_read_ahead, number=10000)
            0.2204863309962093
            >>> timeit(fetch, read_ahead, number=10000)
            0.1121859749982832
            >>> timeit(fetch, string_slicing, number=10000)
            0.0033553699977346696
        
        Read-ahead buffering can reduce runtime by 1/2 for sequential accesses to buffered regions.
        
        Complements and reverse complements just like DNA
        
        .. code:: python
        
            >>> genes['NM_001282543.1'][200:230].complement
            >NM_001282543.1 (complement):201-230
            GAGCAAGGCGCGGGCGGTACCTTGGCCTAC
        
            >>> genes['NM_001282543.1'][200:230].reverse
            >NM_001282543.1:230-201
            GTAGGCCAAGGTACCGCCCGCGCCTTGCTC
        
            >>> -genes['NM_001282543.1'][200:230]
            >NM_001282543.1 (complement):230-201
            CATCCGGTTCCATGGCGGGCGCGGAACGAG
        
        Custom key functions provide cleaner access:
        
        .. code:: python
        
            >>> from pyfaidx import Fasta
            >>> genes = Fasta('tests/data/genes.fasta', key_function = lambda x: x.split('.')[0])
            >>> genes.keys()
            dict_keys(['NR_104212', 'NM_001282543', 'XM_005249644', 'XM_005249645', 'NR_104216', 'XM_005249643', 'NR_104215', 'KF435150', 'AB821309', 'NM_001282549', 'XR_241081', 'KF435149', 'XR_241079', 'NM_000465', 'XM_005265508', 'XR_241080', 'XM_005249642', 'NM_001282545', 'XM_005265507', 'NM_001282548'])
            >>> genes['NR_104212'][:10]
            >NR_104212:1-10
            CCCCGCCCCT
        
        Or just get a Python string:
        
        .. code:: python
        
            >>> from pyfaidx import Fasta
            >>> genes = Fasta('tests/data/genes.fasta', as_raw=True)
            >>> genes
            Fasta("tests/data/genes.fasta", as_raw=True)
        
            >>> genes['NM_001282543.1'][200:230]
            CTCGTTCCGCGCCCGCCATGGAACCGGATG
        
        You can also perform line-based iteration, receiving the sequence lines as they appear in the FASTA file:
        
        .. code:: python
        
            >>> from pyfaidx import Fasta
            >>> genes = Fasta('tests/data/genes.fasta')
            >>> for line in genes['NM_001282543.1']:
            ...   print(line)
            CCCCGCCCCTCTGGCGGCCCGCCGTCCCAGACGCGGGAAGAGCTTGGCCGGTTTCGAGTCGCTGGCCTGC
            AGCTTCCCTGTGGTTTCCCGAGGCTTCCTTGCTTCCCGCTCTGCGAGGAGCCTTTCATCCGAAGGCGGGA
            CGATGCCGGATAATCGGCAGCCGAGGAACCGGCAGCCGAGGATCCGCTCCGGGAACGAGCCTCGTTCCGC
            ...
        
        .. role:: red
        
        If you want to modify the contents of your FASTA file in-place, you can use the `mutable` argument.
        Any portion of the FastaRecord can be replaced with an equivalent-length string.
        :red:`Warning`: *This will change the contents of your file immediately and permanently:*
        
        .. code:: python
        
            >>> genes = Fasta('tests/data/genes.fasta', mutable=True)
            >>> type(genes['NM_001282543.1'])
            <class 'pyfaidx.MutableFastaRecord'>
        
            >>> genes['NM_001282543.1'][:10]
            >NM_001282543.1:1-10
            CCCCGCCCCT
            >>> genes['NM_001282543.1'][:10] = 'NNNNNNNNNN'
            >>> genes['NM_001282543.1'][:15]
            >NM_001282543.1:1-15
            NNNNNNNNNNCTGGC
        
        
        It also provides a command-line script:
        
        cli script: faidx
        ~~~~~~~~~~~~~~~~~
        
        For usage type ``faidx -h``.
        
        .. code:: bash
        
            $ faidx tests/data/genes.fasta NM_001282543.1:201-210 NM_001282543.1:300-320
            >NM_001282543.1:201-210
            CTCGTTCCGC
            >NM_001282543.1:300-320
            GTAATTGTGTAAGTGACTGCA
        
            $ faidx --no-names tests/data/genes.fasta NM_001282543.1:201-210 NM_001282543.1:300-320
            CTCGTTCCGC
            GTAATTGTGTAAGTGACTGCA
        
            $ faidx --complement tests/data/genes.fasta NM_001282543.1:201-210
            >NM_001282543.1:201-210 (complement)
            GAGCAAGGCG
        
            $ faidx --reverse tests/data/genes.fasta NM_001282543.1:201-210
            >NM_001282543.1:210-201
            CGCCTTGCTC
        
            $ faidx --reverse --complement tests/data/genes.fasta NM_001282543.1:201-210
            >NM_001282543.1:210-201 (complement)
            GCGGAACGAG
        
            $ faidx tests/data/genes.fasta NM_001282543.1
            >NM_001282543.1:1-5466
            CCCCGCCCCT........
            ..................
            ..................
            ..................
        
            $ faidx --lazy tests/data/genes.fasta NM_001282543.1:5460-5480
            >NM_001282543.1:5460-5480
            AAAAAAANNNNNNNNNNNNNN
        
            $ faidx --lazy --default-seq='Q' tests/data/genes.fasta NM_001282543.1:5460-5480
            >NM_001282543.1:5460-5480
            AAAAAAAQQQQQQQQQQQQQQ
        
            $ faidx tests/data/genes.fasta --bed regions.bed
            ...
        
            $ faidx --stats tests/data/genes.fasta
            AB821309.1	3510
            KF435150.1	481
            KF435149.1	642
            NR_104216.1	4573
            NR_104215.1	5317
            NR_104212.1	5374
            NM_001282545.1	4170
            NM_001282543.1	5466
            NM_000465.3	5523
            NM_001282549.1	3984
            NM_001282548.1	4113
            XM_005249645.1	2752
            XM_005249644.1	3004
            XM_005249643.1	3109
            XM_005249642.1	3097
            XM_005265508.1	2794
            XM_005265507.1	2848
            XR_241081.1	1009
            XR_241080.1	4884
            XR_241079.1	2819
        
            $ faidx --split-files tests/data/genes.fasta
            $ ls
            AB821309.1.fasta	NM_001282549.1.fasta	XM_005249645.1.fasta
            KF435149.1.fasta	NR_104212.1.fasta	XM_005265507.1.fasta
            KF435150.1.fasta	NR_104215.1.fasta	XM_005265508.1.fasta
            NM_000465.3.fasta	NR_104216.1.fasta	XR_241079.1.fasta
            NM_001282543.1.fasta	XM_005249642.1.fasta	XR_241080.1.fasta
            NM_001282545.1.fasta	XM_005249643.1.fasta	XR_241081.1.fasta
            NM_001282548.1.fasta	XM_005249644.1.fasta
        
            $ faidx --delimiter='_' tests/data/genes.fasta 000465.3
            >000465.3
            CCCCGCCCCTCTGGCGGCCCGCCGTCCCAGACGCGGGAAGAGCTTGGCCGGTTTCGAGTCGCTGGCCTGC
            AGCTTCCCTGTGGTTTCCCGAGGCTTCCTTGCTTCCCGCTCTGCGAGGAGCCTTTCATCCGAAGGCGGGA
            .......
        
        
        Similar syntax as ``samtools faidx``
        
        
        A lower-level Faidx class is also available:
        
        .. code:: python
        
            >>> from pyfaidx import Faidx
            >>> fa = Faidx('genes.fa')  # can return str with as_raw=True
            >>> fa.index
            OrderedDict([('AB821309.1', IndexRecord(rlen=3510, offset=12, lenc=70, lenb=71)), ('KF435150.1', IndexRecord(rlen=481, offset=3585, lenc=70, lenb=71)),... ])
        
            >>> fa.index['AB821309.1'].rlen
            3510
        
            fa.fetch('AB821309.1', 1, 10)  # these are 1-based genomic coordinates
            >AB821309.1:1-10
            ATGGTCAGCT
        
        
        -  If the FASTA file is not indexed, when ``Faidx`` is initialized the
           ``build_index`` method will automatically run, and
           the index will be written to "filename.fa.fai" with ``write_fai()``.
           where "filename.fa" is the original FASTA file.
        -  Start and end coordinates are 1-based.
        
        
        Changelog
        -------
        
        Please see the `releases <https://github.com/mdshw5/pyfaidx/releases>`_ for a
        comprehensive list of version changes.
        
        Acknowledgements
        ----------------
        
        This project is freely licensed by the author, `Matthew
        Shirley <http://mattshirley.com>`_, and was completed under the
        mentorship and financial support of Drs. `Sarah
        Wheelan <http://sjwheelan.som.jhmi.edu>`_ and `Vasan
        Yegnasubramanian <http://yegnalab.onc.jhmi.edu>`_ at the Sidney Kimmel
        Comprehensive Cancer Center in the Department of Oncology.
        
        .. |Travis| image:: https://travis-ci.org/mdshw5/pyfaidx.svg?branch=master
            :target: https://travis-ci.org/mdshw5/pyfaidx
        
        .. |PyPI| image:: https://img.shields.io/pypi/v/pyfaidx.svg?branch=master
            :target: https://pypi.python.org/pypi/pyfaidx
        
        .. |Landscape| image:: https://landscape.io/github/mdshw5/pyfaidx/master/landscape.svg
           :target: https://landscape.io/github/mdshw5/pyfaidx/master
           :alt: Code Health
        
        .. |Coveralls| image:: https://coveralls.io/repos/mdshw5/pyfaidx/badge.svg?branch=master
           :target: https://coveralls.io/r/mdshw5/pyfaidx?branch=master
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Provides: p
Provides: y
Provides: f
Provides: a
Provides: i
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Provides: x
