https://github.com/lucacappelletti94/ucsc_genomes_downloader
Python package to quickly download genomes from the UCSC.
https://github.com/lucacappelletti94/ucsc_genomes_downloader
Last synced: 12 months ago
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Python package to quickly download genomes from the UCSC.
- Host: GitHub
- URL: https://github.com/lucacappelletti94/ucsc_genomes_downloader
- Owner: LucaCappelletti94
- License: mit
- Created: 2019-05-27T06:16:41.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2022-04-29T08:14:07.000Z (almost 4 years ago)
- Last Synced: 2025-05-07T23:45:26.558Z (12 months ago)
- Language: Python
- Size: 590 KB
- Stars: 7
- Watchers: 1
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.rst
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
README
UCSC Genomes Downloader
=========================================================================================
|python_version| |pip| |downloads|
Python package to quickly download and process genomes from the UCSC website.
How do I install this package?
----------------------------------------------
As usual, just download it using pip:
.. code:: shell
pip install ucsc_genomes_downloader
Getting COVID-19 Genome
----------------------------------------------
To download the COVID19 genome just run:
.. code:: python
from ucsc_genomes_downloader import Genome
covid = Genome("wuhCor1")
genome = covid["NC_045512v2"]
Usage examples
--------------
Simply instantiate a new genome
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
To download and load into memory the chromosomes of a given genomic assembly
you can use the following code snippet:
.. code:: python
from ucsc_genomes_downloader import Genome
hg19 = Genome(assembly="hg19")
Downloading selected chromosomes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
If you want to select a subset of chromosomes to be downloaded
you can use the attribute "chromosomes":
.. code:: python
from ucsc_genomes_downloader import Genome
hg19 = Genome("hg19", chromosomes=["chr1", "chr2"])
Getting gaps regions
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The method returns a DataFrame in bed-like format
that contains the regions where only n or N nucleotides
are present.
.. code:: python
all_gaps = hg19.gaps() # Returns gaps (region formed of Ns) for all chromosomes
# Returns gaps for chromosome chrM
chrM_gaps = hg19.gaps(chromosomes=["chrM"])
Getting filled regions
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The method returns a DataFrame in bed-like format
that contains the regions where no unknown nucleotides
are present, basically the complementary
of the gaps method.
.. code:: python
all_filled = hg19.filled() # Returns filled for all chromosomes
# Returns filled for chromosome chrM
chrM_filled = hg19.filled(chromosomes=["chrM"])
Removing genome's cache
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
To delete the cache of the genome, including chromosomes
and metadata you can use the delete method:
.. code:: python
hg19.delete()
Genome objects representation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
When printed, a Genome object has a human-readable representation.
This allows you to print lists of Genome objects as follows:
.. code:: python
print([
hg19,
hg38,
mm10
])
# >>> [
# Human, Homo sapiens, hg19, 2009-02-28, 25 chromosomes,
# Human, Homo sapiens, hg38, 2013-12-29, 25 chromosomes,
# Mouse, Mus musculus, mm10, 2011-12-29, 22 chromosomes
# ]
Obtaining a given bed file sequences
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Given a pandas DataFrame in bed-like format, you can obtain
the corresponding genomic sequences for the loaded assembly
using the bed_to_sequence method:
.. code:: python
my_bed = pd.read_csv("path/to/my/file.bed", sep="\t")
sequences = hg19.bed_to_sequence(my_bed)
Properties
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A Genome object has the following properties:
.. code:: python
hg19.assembly # Returns "hg19"
hg19.date # Returns "2009-02-28" as datetime object
hg19.organism # Returns "Human"
hg19.scientific_name # Returns "Homo sapiens"
hg19.description # Returns the brief description as provided from UCSC
hg19.path # Returns path where genome is cached
Utilities
-------------------------------
Retrieving a list of the available genomes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
You can get a complete list of the genomes available
from the UCSC website with the following method:
.. code:: python
from ucsc_genomes_downloader.utils import get_available_genomes
all_genomes = get_available_genomes()
Tessellating bed files
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Create a tessellation of a given size of a given bed-like pandas dataframe.
Available alignments are to the left, right or center.
.. code:: python
from ucsc_genomes_downloader.utils import tessellate_bed
import pandas as pd
my_bed = pd.read_csv("path/to/my/file.bed", sep="\t")
tessellated = tessellate_bed(
my_bed,
window_size=200,
alignment="left"
)
Expand bed files regions
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Expand a given dataframe in bed-like format using selected alignment.
Available alignments are to the left, right or center.
.. code:: python
from ucsc_genomes_downloader.utils import expand_bed_regions
import pandas as pd
my_bed = pd.read_csv("path/to/my/file.bed", sep="\t")
expanded = expand_bed_regions(
my_bed,
window_size=1000,
alignment="left"
)
Wiggle bed files regions
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Generate new bed regions based on a given bed file by wiggling the
initial regions.
.. code:: python
from ucsc_genomes_downloader.utils import wiggle_bed_regions
import pandas as pd
my_bed = pd.read_csv("path/to/my/file.bed", sep="\t")
expanded = wiggle_bed_regions(
my_bed,
max_wiggle_size=100, # Maximum amount to wiggle region
wiggles=10, # Number of wiggled samples to introduce
seed=42 # Random seed for reproducibility
)
.. _hg19: https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.13/
.. |pip| image:: https://badge.fury.io/py/ucsc-genomes-downloader.svg
:target: https://badge.fury.io/py/ucsc-genomes-downloader
:alt: Pypi project
.. |downloads| image:: https://pepy.tech/badge/ucsc-genomes-downloader
:target: https://pepy.tech/badge/ucsc-genomes-downloader
:alt: Pypi total project downloads
.. |python_version| image:: https://img.shields.io/badge/python-3.x-blue
:alt: Supported Python Versions