Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/saketkc/pyseqlogo
Python package to plot sequence logos
https://github.com/saketkc/pyseqlogo
motif motif-analysis sequence-logo tfs
Last synced: about 4 hours ago
JSON representation
Python package to plot sequence logos
- Host: GitHub
- URL: https://github.com/saketkc/pyseqlogo
- Owner: saketkc
- License: mit
- Created: 2017-10-14T16:49:38.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2023-09-21T20:49:05.000Z (about 1 year ago)
- Last Synced: 2024-11-01T02:51:48.438Z (7 days ago)
- Topics: motif, motif-analysis, sequence-logo, tfs
- Language: Python
- Homepage: https://www.saket-choudhary.me/pyseqlogo/
- Size: 10.6 MB
- Stars: 29
- Watchers: 3
- Forks: 18
- Open Issues: 3
-
Metadata Files:
- Readme: README.rst
- Changelog: HISTORY.rst
- Contributing: CONTRIBUTING.rst
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
=========
pyseqlogo
=========
.. figure:: https://img.shields.io/pypi/v/pyseqlogo.svg
:target: https://pypi.python.org/pypi/pyseqlogo
.. figure:: https://img.shields.io/travis/saketkc/pyseqlogo.svg
:target: https://travis-ci.org/saketkc/pyseqlogo
.. figure:: https://pyup.io/repos/github/saketkc/pyseqlogo/shield.svg
:target: https://pyup.io/repos/github/saketkc/pyseqlogo/
:alt: Updates
Python package to plot sequence logos
* Free software: MIT license
* Documentation: http://saketkc.github.io/pyseqlogo
* Example Notebook: https://github.com/saketkc/pyseqlogo/blob/master/notebooks/Example01.ipynb
.. code:: python
from pyseqlogo.pyseqlogo import draw_logo, setup_axis
.. code:: python
ALL_SCORES1 = [[('C', 0.02247014831444764),
('T', 0.057903843733384308),
('A', 0.10370837683591219),
('G', 0.24803586793255664)],
[('T', 0.046608227674354567),
('G', 0.048827667087419063),
('A', 0.084338697696451109),
('C', 0.92994511407402669)],
[('G', 0.0),
('T', 0.011098351287382456),
('A', 0.022196702574764911),
('C', 1.8164301607015951)],
[('C', 0.020803153636453006),
('T', 0.078011826136698756),
('G', 0.11268374886412044),
('A', 0.65529933954826969)],
[('T', 0.017393530660176126),
('A', 0.030438678655308221),
('G', 0.22611589858228964),
('C', 0.45078233627623127)],
[('G', 0.022364103549245576),
('A', 0.043412671595594352),
('T', 0.097349627214363091),
('C', 0.1657574733649966)],
[('C', 0.03264675899941203),
('T', 0.045203204768416654),
('G', 0.082872542075430544),
('A', 1.0949220710572034)],
[('C', 0.0),
('T', 0.0076232429756614498),
('A', 0.011434864463492175),
('G', 1.8867526364762088)],
[('C', 0.0018955903000026028),
('T', 0.0094779515000130137),
('A', 0.35637097640048931),
('G', 0.58005063180079641)],
[('A', 0.01594690817903021),
('C', 0.017541598996933229),
('T', 0.2774762023151256),
('G', 0.48638069946042134)],
[('A', 0.003770051401807444),
('C', 0.0075401028036148881),
('T', 0.011310154205422331),
('G', 1.8624053924928772)],
[('C', 0.036479877757360731),
('A', 0.041691288865555121),
('T', 0.072959755514721461),
('G', 1.1517218549109602)],
[('G', 0.011831087684038642),
('T', 0.068620308567424126),
('A', 0.10174735408273231),
('C', 1.0009100180696691)],
[('C', 0.015871770937774379),
('T', 0.018757547471915176),
('A', 0.32176408355669878),
('G', 0.36505073156881074)],
[('A', 0.022798100897300954),
('T', 0.024064662058262118),
('G', 0.24571286522646588),
('C', 0.34070495229855319)]]
Default mode is bits
====================
.. code:: python
plt.rcParams['figure.dpi'] = 300
fig, axarr = draw_logo(ALL_SCORES1)
fig.tight_layout()
.. figure:: examples/output_3_0.png
:align: center
:width: 100%
:figclass: align center
Colorscheme
===========
.. code:: python
plt.rcParams['figure.dpi'] = 300
fig, axarr = draw_logo(ALL_SCORES1, data_type='bits', colorscheme='meme')
fig.tight_layout()
.. figure:: docs/images/output_5_0.png
:align: center
:width: 100%
:figclass: align center
Counts as input
===============
.. code:: python
counts = {'A' : [3,4,5,6], 'C': [2,3,1,1], 'T': [2,1,3,1], 'G': [3,2,1,2]}
fig, axarr = draw_logo(counts, data_type='counts', yaxis='probability')
fig.tight_layout()
.. figure:: docs/images/output_7_0.png
:align: center
:width: 100%
:figclass: align center
Different font!
===============
.. code:: python
fig, axarr = draw_logo(counts, data_type='counts', yaxis='probability', fontfamily='Comic Sans MS')
fig.tight_layout()
.. figure:: docs/images/output_9_0.png
:align: center
:width: 100%
:figclass: align center
Plot conservation scores
========================
.. code:: python
ALL_SCORES = [[('G', 0.1),
('A', 0.1),
('C', 0.31312908494534769),
('T', 0.84220926295645249)]] * 4
stem_scores = np.random.rand(4)
fig, axarr = draw_logo(ALL_SCORES, data_type='bits', nrow= 2,ncol=1)
axarr[1,0].stem(range(1, len(ALL_SCORES)+1), stem_scores)
setup_axis(axarr[1,0], axis='y', majorticks=1, minorticks=0.1)
fig.tight_layout()
.. figure:: docs/images/output_11_0.png
:align: center
:width: 100%
:figclass: align center
Credits
---------
This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
.. _notebook: notebooks/Example01.ipynb
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage