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Pozdniakova et al. 2023

This repository contains Jupyter notebooks describing cloning using Python, Jupyter notebooks and pydna.

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The notebooks and other files in this repository accompany the publication:

button

Adams, A. A., Ball, B, & Carter, C. C. (2000). An example of a placeholder reference. Journal of Examples, 23(4), 245-259.

PubMed website

DOI

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The notebooks can be visualized in a number of ways.

The notebooks (.ipynb) can be viewed directly on Github or through the nbviewer service here

The Jupyter Notebook Viewer for chrome is free and very useful to rapidly view notebooks in the browser.

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Significant files

index

pMEC1049

Pydna boilerplate code

nbval_examples

The index.ipynb notebook is the place to start as it has links to the other notebooks.

Each notebook contain links (usually in the end) to the resulting sequences in Genbank flat file format.

These notebooks are tested on the github action build service.

This means that the notebook outputs are re-executed and compared with saved results once per week to ensure reproducibility.

If the badge below is green, all tests gave the expected results.

test jupyter notebooks

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How to use this repository

This repository was made to facilitate reproducing Jupyter notebooks online in a GitHub repository.

  1. Create a GitHub account if you do not already have one
  2. Click on the button at the top of this screen to make you own copy

Using Git

These steps require having Git installed. This is the recommended way.

  1. Clone the repository to you own computer.
  2. Replace the notebooks in the notebooks folder with your notebooks and add all other files needed to run them
  3. Run the notebooks using the test_all_notebooks.sh script
  4. Add dependencies to the environment.yml if necessary
  5. Commit and push

Using GitHub

These steps do not require Git.

  1. Run and save your notebooks on you local computer
  2. Navigate to the notebooks folder in your repository
  3. Use the Addfile -> Upload files button at the upper right corner to upload your notebooks and all other files needed to run them.
  4. Edit the environment.yml if necessary. This can be done online.
  5. Click on each original file that you do not want to have the option to delete them.

Automatic testing

The notebooks are set up to be tested once per week by running the test_all_notebooks.sh script. This can be changed in the .github/workflows/test_notebooks_workflow.yml file.

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Funding

We are grateful for funding from:

Fundação para a Ciência e Tecnologia Portugal (FCT) through project FatVal PTDC/EAM-AMB/032506/2017 funded by national funds through the FCT I.P. and by the ERDF through the COMPETE2020 – Programa Operacional Competitividade e Internacionalizacão (POCI).

CBMA was supported by the strategic program UIDB/04050/2020 funded by national funds through the FCT I.P.