Pyfaidx Save
Efficient pythonic random access to fasta subsequences
Project README
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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 using a samtools
compatible index. The pyfaidx module is API compatible with the pygr_ seqdb module.
A command-line script "faidx_" is installed alongside the pyfaidx module, and
facilitates complex manipulation of FASTA files without any programming knowledge.
.. _pygr: https://github.com/cjlee112/pygr
If you use pyfaidx in your publication, please cite:
Shirley MD, Ma Z, Pedersen B, Wheelan S. Efficient "pythonic" access to FASTA files using pyfaidx <https://dx.doi.org/10.7287/peerj.preprints.970v1>_. PeerJ PrePrints 3:e1196. 2015.
.. _Shirley MD: http://github.com/mdshw5
.. _Ma Z: http://github.com/azalea
.. _Pedersen B: http://github.com/brentp
.. _Wheelan S: http://github.com/swheelan
Installation
This package is tested under Linux and macOS using Python 3.7+, and and is available from the PyPI:
::
pip install pyfaidx # add --user if you don't have root
or download a release <https://github.com/mdshw5/pyfaidx/releases>_ and:
::
pip install .
If using pip install --user make sure to add /home/$USER/.local/bin to your $PATH (on linux) or /Users/$USER/Library/Python/{python version}/bin (on macOS) if you want to run the faidx script.
Python 2.6 and 2.7 users may choose to use a package version from v0.7.2 <https://github.com/mdshw5/pyfaidx/releases/tag/v0.7.2.2>_ or earier.
Usage
.. 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'
# Start attributes are 1-based
>>> genes['NM_001282543.1'][200:230].start
201
# End attributes are 0-based
>>> genes['NM_001282543.1'][200:230].end
230
>>> genes['NM_001282543.1'][200:230].fancy_name
'NM_001282543.1:201-230'
>>> len(genes['NM_001282543.1'])
5466
Note that start and end coordinates of Sequence objects are [1, 0]. This can be changed to [0, 0] by passing one_based_attributes=False to Fasta or Faidx. This argument only affects the Sequence .start/.end attributes, and has no effect on slicing coordinates.
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........
- Slicing start and end coordinates are 0-based, just like Python sequences.
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
Fasta objects can also be accessed using method calls:
.. code:: python
>>> genes.get_seq('NM_001282543.1', 201, 210)
>NM_001282543.1:201-210
CTCGTTCCGC
>>> genes.get_seq('NM_001282543.1', 201, 210, rc=True)
>NM_001282543.1 (complement):210-201
GCGGAACGAG
Spliced sequences can be retrieved from a list of [start, end] coordinates: TODO update this section
.. code:: python
# new in v0.5.1
segments = [[1, 10], [50, 70]]
>>> genes.get_spliced_seq('NM_001282543.1', segments)
>gi|543583786|ref|NM_001282543.1|:1-70
CCCCGCCCCTGGTTTCGAGTCGCTGGCCTGC
.. _keyfn:
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
You can specify a character to split names on, which will generate additional entries:
.. code:: python
>>> from pyfaidx import Fasta
>>> genes = Fasta('tests/data/genes.fasta', split_char='.', duplicate_action="first") # default duplicate_action="stop"
>>> genes.keys()
dict_keys(['.1', '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'])
If your key_function or split_char generates duplicate entries, you can choose what action to take:
.. code:: python
# new in v0.4.9
>>> genes = Fasta('tests/data/genes.fasta', split_char="|", duplicate_action="longest")
>>> genes.keys()
dict_keys(['gi', '563317589', 'dbj', 'AB821309.1', '', '557361099', 'gb', 'KF435150.1', '557361097', 'KF435149.1', '543583796', 'ref', 'NR_104216.1', '543583795', 'NR_104215.1', '543583794', 'NR_104212.1', '543583788', 'NM_001282545.1', '543583786', 'NM_001282543.1', '543583785', 'NM_000465.3', '543583740', 'NM_001282549.1', '543583738', 'NM_001282548.1', '530384540', 'XM_005249645.1', '530384538', 'XM_005249644.1', '530384536', 'XM_005249643.1', '530384534', 'XM_005249642.1', '530373237','XM_005265508.1', '530373235', 'XM_005265507.1', '530364726', 'XR_241081.1', '530364725', 'XR_241080.1', '530364724', 'XR_241079.1'])
Filter functions (returning True) limit the index:
.. code:: python
# new in v0.3.8
>>> from pyfaidx import Fasta
>>> genes = Fasta('tests/data/genes.fasta', filt_function = lambda x: x[0] == 'N')
>>> genes.keys()
dict_keys(['NR_104212', 'NM_001282543', 'NR_104216', 'NR_104215', 'NM_001282549', 'NM_000465', 'NM_001282545', 'NM_001282548'])
>>> genes['XM_005249644']
KeyError: XM_005249644 not in tests/data/genes.fasta.
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 make sure that you always receive an uppercase sequence, even if your fasta file has lower case
.. code:: python
>>> from pyfaidx import Fasta
>>> reference = Fasta('tests/data/genes.fasta.lower', sequence_always_upper=True)
>>> reference['gi|557361099|gb|KF435150.1|'][1:70]
>gi|557361099|gb|KF435150.1|:2-70
TGACATCATTTTCCACCTCTGCTCAGTGTTCAACATCTGACAGTGCTTGCAGGATCTCTCCTGGACAAA
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
...
Sequence names are truncated on any whitespace. This is a limitation of the indexing strategy. However, full names can be recovered:
.. code:: python
# new in v0.3.7
>>> from pyfaidx import Fasta
>>> genes = Fasta('tests/data/genes.fasta')
>>> for record in genes:
... print(record.name)
... print(record.long_name)
...
gi|563317589|dbj|AB821309.1|
gi|563317589|dbj|AB821309.1| Homo sapiens FGFR2-AHCYL1 mRNA for FGFR2-AHCYL1 fusion kinase protein, complete cds
gi|557361099|gb|KF435150.1|
gi|557361099|gb|KF435150.1| Homo sapiens MDM4 protein variant Y (MDM4) mRNA, complete cds, alternatively spliced
gi|557361097|gb|KF435149.1|
gi|557361097|gb|KF435149.1| Homo sapiens MDM4 protein variant G (MDM4) mRNA, complete cds
...
# new in v0.4.9
>>> from pyfaidx import Fasta
>>> genes = Fasta('tests/data/genes.fasta', read_long_names=True)
>>> for record in genes:
... print(record.name)
...
gi|563317589|dbj|AB821309.1| Homo sapiens FGFR2-AHCYL1 mRNA for FGFR2-AHCYL1 fusion kinase protein, complete cds
gi|557361099|gb|KF435150.1| Homo sapiens MDM4 protein variant Y (MDM4) mRNA, complete cds, alternatively spliced
gi|557361097|gb|KF435149.1| Homo sapiens MDM4 protein variant G (MDM4) mRNA, complete cds
Records can be accessed efficiently as numpy arrays:
.. code:: python
# new in v0.5.4
>>> from pyfaidx import Fasta
>>> import numpy as np
>>> genes = Fasta('tests/data/genes.fasta')
>>> np.asarray(genes['NM_001282543.1'])
array(['C', 'C', 'C', ..., 'A', 'A', 'A'], dtype='|S1')
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.
.. 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
The FastaVariant class provides a way to integrate single nucleotide variant calls to generate a consensus sequence.
.. code:: python
# new in v0.4.0
>>> consensus = FastaVariant('tests/data/chr22.fasta', 'tests/data/chr22.vcf.gz', het=True, hom=True)
RuntimeWarning: Using sample NA06984 genotypes.
>>> consensus['22'].variant_sites
(16042793, 21833121, 29153196, 29187373, 29187448, 29194610, 29821295, 29821332, 29993842, 32330460, 32352284)
>>> consensus['22'][16042790:16042800]
>22:16042791-16042800
TCGTAGGACA
>>> Fasta('tests/data/chr22.fasta')['22'][16042790:16042800]
>22:16042791-16042800
TCATAGGACA
>>> consensus = FastaVariant('tests/data/chr22.fasta', 'tests/data/chr22.vcf.gz', sample='NA06984', het=True, hom=True, call_filter='GT == "0/1"')
>>> consensus['22'].variant_sites
(16042793, 29187373, 29187448, 29194610, 29821332)
You can also specify paths using pathlib.Path objects.
.. code:: python
#new in v0.7.1
>>> from pyfaidx import Fasta
>>> from pathlib import Path
>>> genes = Fasta(Path('tests/data/genes.fasta'))
>>> genes
Fasta("tests/data/genes.fasta")
Accessing fasta files from filesystem_spec <https://filesystem-spec.readthedocs.io>_ filesystems:
.. code:: python
# new in v0.7.0
# pip install fsspec s3fs
>>> import fsspec
>>> from pyfaidx import Fasta
>>> of = fsspec.open("s3://broad-references/hg19/v0/Homo_sapiens_assembly19.fasta", anon=True)
>>> genes = Fasta(of)
.. _faidx:
It also provides a command-line script:
cli script: faidx
.. code:: bash
Fetch sequences from FASTA. If no regions are specified, all entries in the
input file are returned. Input FASTA file must be consistently line-wrapped,
and line wrapping of output is based on input line lengths.
positional arguments:
fasta FASTA file
regions space separated regions of sequence to fetch e.g.
chr1:1-1000
optional arguments:
-h, --help show this help message and exit
-b BED, --bed BED bed file of regions (zero-based start coordinate)
-o OUT, --out OUT output file name (default: stdout)
-i {bed,chromsizes,nucleotide,transposed}, --transform {bed,chromsizes,nucleotide,transposed} transform the requested regions into another format. default: None
-c, --complement complement the sequence. default: False
-r, --reverse reverse the sequence. default: False
-a SIZE_RANGE, --size-range SIZE_RANGE
selected sequences are in the size range [low, high]. example: 1,1000 default: None
-n, --no-names omit sequence names from output. default: False
-f, --full-names output full names including description. default: False
-x, --split-files write each region to a separate file (names are derived from regions)
-l, --lazy fill in --default-seq for missing ranges. default: False
-s DEFAULT_SEQ, --default-seq DEFAULT_SEQ
default base for missing positions and masking. default: None
-d DELIMITER, --delimiter DELIMITER
delimiter for splitting names to multiple values (duplicate names will be discarded). default: None
-e HEADER_FUNCTION, --header-function HEADER_FUNCTION
python function to modify header lines e.g: "lambda x: x.split("|")[0]". default: lambda x: x.split()[0]
-u {stop,first,last,longest,shortest}, --duplicates-action {stop,first,last,longest,shortest}
entry to take when duplicate sequence names are encountered. default: stop
-g REGEX, --regex REGEX
selected sequences are those matching regular expression. default: .*
-v, --invert-match selected sequences are those not matching 'regions' argument. default: False
-m, --mask-with-default-seq
mask the FASTA file using --default-seq default: False
-M, --mask-by-case mask the FASTA file by changing to lowercase. default: False
-e HEADER_FUNCTION, --header-function HEADER_FUNCTION
python function to modify header lines e.g: "lambda x: x.split("|")[0]". default: None
--no-rebuild do not rebuild the .fai index even if it is out of date. default: False
--version print pyfaidx version number
Examples:
.. code:: bash
$ faidx -v tests/data/genes.fasta
### Creates an .fai index, but supresses sequence output using --invert-match ###
$ 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 --full-names tests/data/genes.fasta NM_001282543.1:201-210
>NM_001282543.1| Homo sapiens BRCA1 associated RING domain 1 (BARD1), transcript variant 2, mRNA
CTCGTTCCGC
$ 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 --regex "^NM_00128254[35]" genes.fasta
>NM_001282543.1
..................
..................
..................
>NM_001282545.1
..................
..................
..................
$ 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 --transform chromsizes 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
...
$ faidx --transform bed tests/data/genes.fasta
AB821309.1 1 3510
KF435150.1 1 481
KF435149.1 1 642
NR_104216.1 1 4573
NR_104215.1 1 5317
NR_104212.1 1 5374
...
$ faidx --transform nucleotide tests/data/genes.fasta
name start end A T C G N
AB821309.1 1 3510 955 774 837 944 0
KF435150.1 1 481 149 120 103 109 0
KF435149.1 1 642 201 163 129 149 0
NR_104216.1 1 4573 1294 1552 828 899 0
NR_104215.1 1 5317 1567 1738 968 1044 0
NR_104212.1 1 5374 1581 1756 977 1060 0
...
faidx --transform transposed tests/data/genes.fasta
AB821309.1 1 3510 ATGGTCAGCTGGGGTCGTTTCATC...
KF435150.1 1 481 ATGACATCATTTTCCACCTCTGCT...
KF435149.1 1 642 ATGACATCATTTTCCACCTCTGCT...
NR_104216.1 1 4573 CCCCGCCCCTCTGGCGGCCCGCCG...
NR_104215.1 1 5317 CCCCGCCCCTCTGGCGGCCCGCCG...
NR_104212.1 1 5374 CCCCGCCCCTCTGGCGGCCCGCCG...
...
$ 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
.......
$ faidx --size-range 5500,6000 -i chromsizes tests/data/genes.fasta
NM_000465.3 5523
$ faidx -m --bed regions.bed tests/data/genes.fasta
### Modifies tests/data/genes.fasta by masking regions using --default-seq character ###
$ faidx -M --bed regions.bed tests/data/genes.fasta
### Modifies tests/data/genes.fasta by masking regions using lowercase characters ###
$ faidx -e "lambda x: x.split('.')[0]" tests/data/genes.fasta -i bed
AB821309 1 3510
KF435150 1 481
KF435149 1 642
NR_104216 1 4573
NR_104215 1 5317
.......
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.
Support for compressed FASTA
----------------------------
``pyfaidx`` can create and read ``.fai`` indices for FASTA files that have
been compressed using the `bgzip <https://www.htslib.org/doc/bgzip.html>`_
tool from `samtools <http://www.htslib.org/>`_. ``bgzip`` writes compressed
data in a ``BGZF`` format. ``BGZF`` is ``gzip`` compatible, consisting of
multiple concatenated ``gzip`` blocks, each with an additional ``gzip``
header making it possible to build an index for rapid random access. I.e.,
files compressed with ``bgzip`` are valid ``gzip`` and so can be read by
``gunzip``. See `this description
<http://pydoc.net/Python/biopython/1.66/Bio.bgzf/>`_ for more details on
``bgzip``.
Changelog
---------
Please see the `releases <https://github.com/mdshw5/pyfaidx/releases>`_ for a
comprehensive list of version changes.
Known issues
------------
I try to fix as many bugs as possible, but most of this work is supported by a single developer. Please check the `known issues <https://github.com/mdshw5/pyfaidx/issues?utf8=✓&q=is%3Aissue+is%3Aopen+label%3Aknown>`_ for bugs relevant to your work. Pull requests are welcome.
Contributing
------------
Create a new Pull Request with one feature. If you add a new feature, please
create also the relevant test.
To get test running on your machine:
- Create a new virtualenv and install the `dev-requirements.txt`.
pip install -r dev-requirements.txt
- Download the test data running:
python tests/data/download_gene_fasta.py
- Run the tests with
pytests
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.com/mdshw5/pyfaidx.svg?branch=master
:target: https://travis-ci.com/mdshw5/pyfaidx
.. |CI| image:: https://github.com/mdshw5/pyfaidx/actions/workflows/main.yml/badge.svg?branch=master
:target: https://github.com/mdshw5/pyfaidx/actions/workflows/main.yml
.. |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
.. |Coverage| image:: https://codecov.io/gh/mdshw5/pyfaidx/branch/master/graph/badge.svg
:target: https://codecov.io/gh/mdshw5/pyfaidx
.. |Depsy| image:: http://depsy.org/api/package/pypi/pyfaidx/badge.svg
:target: http://depsy.org/package/python/pyfaidx
.. |Appveyor| image:: https://ci.appveyor.com/api/projects/status/80ihlw30a003596w?svg=true
:target: https://ci.appveyor.com/project/mdshw5/pyfaidx
.. |Package| image:: https://github.com/mdshw5/pyfaidx/actions/workflows/pypi.yml/badge.svg
:target: https://github.com/mdshw5/pyfaidx/actions/workflows/pypi.yml
.. |Downloads| image:: https://img.shields.io/pypi/dm/pyfaidx.svg
:target: https://pypi.python.org/pypi/pyfaidx/
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