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https://github.com/edinburgh-genome-foundry/tatapov
:paw_prints: DNA overhang misannealing data for Python
https://github.com/edinburgh-genome-foundry/tatapov
dna-assembly dna-design golden-gate synthetic-biology
Last synced: 29 days ago
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:paw_prints: DNA overhang misannealing data for Python
- Host: GitHub
- URL: https://github.com/edinburgh-genome-foundry/tatapov
- Owner: Edinburgh-Genome-Foundry
- License: mit
- Created: 2018-09-25T20:22:46.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2022-05-06T13:48:27.000Z (over 2 years ago)
- Last Synced: 2024-11-10T02:28:29.575Z (about 1 month ago)
- Topics: dna-assembly, dna-design, golden-gate, synthetic-biology
- Language: Python
- Homepage: https://cuba.genomefoundry.org/view-overhangs-crosstalk
- Size: 50.8 KB
- Stars: 13
- Watchers: 5
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.rst
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README
.. raw:: html
Tatapov
-------.. image:: https://app.travis-ci.com/Edinburgh-Genome-Foundry/tatapov.svg?branch=master
:target: https://app.travis-ci.com/Edinburgh-Genome-Foundry/tatapov
:alt: Travis CI build status.. image:: https://coveralls.io/repos/github/Edinburgh-Genome-Foundry/tatapov/badge.svg?branch=master
:target: https://coveralls.io/github/Edinburgh-Genome-Foundry/tatapov?branch=masterTatapov is a Python library making accessible and easy to explore the DNA
overhang misannealing data from Potapov et al. (2018, `bioRxiv `_) and Pryor et al. (2020, `PLoS ONE `_):*Optimization of Golden Gate assembly through application of ligation
sequence-dependent fidelity and bias profiling.* Vladimir Potapov,
Jennifer L. Ong, Rebecca B. Kucera, Bradley W. Langhorst,
Katharina Bilotti, John M. Pryor, Eric J. Cantor, Barry Canton,
Thomas F. Knight, Thomas C. Evans Jr., Gregory Lohman. bioRxiv (2018)
https://doi.org/10.1101/322297*Enabling one-pot Golden Gate assemblies of unprecedented complexity using
data-optimized assembly design.* John M. Pryor, Vladimir Potapov,
Rebecca B. Kucera, Katharina Bilotti, Eric J. Cantor, Gregory J. S. Lohman.
PLoS ONE (2020) 15(9): e0238592. https://doi.org/10.1371/journal.pone.0238592The Supplementary Material of these papers provide tables of inter-overhang
annealing data in various conditions (01h or 18h incubations at 25C or 37C).
Tatapov provides these tables (it will download them automatically
upon first use) as pandas dataframes, so that they are easy to manipulate.It also provides simple methods to build and plot subsets of the data (plotting
requires Matplotlib installed).Usage example
-------------**Plotting**
.. code:: python
import tatapov
# Get a subset of the data at 25C (1h incubation)
data = tatapov.annealing_data["25C"]["01h"] # a pandas dataframe
overhangs = ["ACGA", "AAAT", "AGAG"]
subset = tatapov.data_subset(data, overhangs, add_reverse=True)# Plot the data subset
ax, _ = tatapov.plot_data(subset, figwidth=5, plot_color="Blues")
ax.figure.tight_layout()
ax.figure.savefig("example.png").. image:: https://raw.githubusercontent.com/Edinburgh-Genome-Foundry/tatapov/master/images/tatapov_example.png
In the plot above, if you see anything else than the square pairs around the
diagonal, it means there is cross-talking between your overhangs (so risk of misannealing).
If one of these diagonal square pairs appears lighter than the others, it means that
the corresponding overhang has weak self-annealing (risk of having no assembly).
A color square in the diagonal means that the overhang can anneal with itself (palindromic).
The Matplotlib colormap is specified with the `plot_color` parameter.The following datasets are available (see the publications for more details):
.. code:: python
# Potapov 2018:
tatapov.annealing_data[temperature][time]
# where temperature is '25C' or '37C', and time is '01h' or '18h'# Pryor 2020 (all 01h):
tatapov.annealing_data['37C'][enzyme]
# where enzyme is one of:
# '2020_01h_BsaI', '2020_01h_BsmBI', '2020_01h_Esp3I' or '2020_01h_BbsI'**Identifying weak self-annealing overhangs**
.. code:: python
import tatapov
annealing_data = tatapov.annealing_data['37C']['01h']
# Compute a dictionary {overhang: self-annealing score in 0-1}
relative_self_annealing = tatapov.relative_self_annealings(annealing_data)weak_self_annealing_overhangs = [
overhang
for overhang, self_annealing in relative_self_annealing.items()
if self_annealing < 0.4
]**Identifying overhang pairs with significant cross-talking**
.. code:: python
import tatapov
annealing_data = tatapov.annealing_data['37C']['01h']
# Compute a dictionary {overhang_pair: cross-talking score in 0-1}
cross_annealings = tatapov.cross_annealings(annealing_data)high_cross_annealing_pairs = [
overhang_pair
for overhang_pair, cross_annealing in cross_annealings.items()
if cross_annealing > 0.08
]Installation
------------You can install Tatapov through PIP:
.. code::
pip install tatapov
Alternatively, you can unzip the sources in a folder and type
.. code::
python setup.py install
License = MIT
-------------Tatapov is an open-source software originally written at the Edinburgh Genome
Foundry by `Zulko `_ and
`released on Github `_
under the MIT licence (Copyright 2018 Edinburgh Genome Foundry). Everyone is welcome
to contribute !Please contact us if there is any issue regarding copyright (there shouldn't be
as the repository does not contain any data, and the paper data is free to
download).More biology software
---------------------.. image:: https://raw.githubusercontent.com/Edinburgh-Genome-Foundry/Edinburgh-Genome-Foundry.github.io/master/static/imgs/logos/egf-codon-horizontal.png
:target: https://edinburgh-genome-foundry.github.io/Tatapov is part of the `EGF Codons `_
synthetic biology software suite for DNA design, manufacturing and validation.