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Welcome to the RegSeq wiki! Use the navigation bar on the right-hand side of this page to read details about the Reg-Seq protocol.

Visit the Code section of this repository to see the README file.

Notes on this Wiki Protocol

Experimental Caveats

This Wiki documents all of the steps necessary to perform the Reg-Seq protocol. We discuss two ways to perform Reg-Seq; one method clones DNA libraries onto a plasmid (pJK14) and expresses the libraries from this plasmid, whereas a second method is to integrate and express DNA libraries from the E. coli genome. The differences between these protocols are clearly annotated in the different Wiki pages. However, we have not performed Reg-Seq on genome-integrated libraries. We have only performed the Reg-Seq protocol on DNA libraries expressed from plasmids. Thus, any discussion on the genome-integrated methods should be taken for what they really are; an experimental possibility, not an experimental reality.

Installation

To reproduce this work, you will need to use the RegSeq module -- a homegrown Python software package written explicitly for this work. We recommend having installed Anaconda3. The package relies on the mpathic package, a software package for quantitative modeling of massively parallel experiments and developed by GitHub user jbkinney. A link to the GitHub page for the mpathic package is available here (it does not have to be downloaded here). mpathic relies on Python 3.6.9. Since this is not the most recent Python version, it is very likely that a new Python environment is necessary. To create this environment, simply navigate into the RegSeq/ folder and run the following line in the terminal:

conda env create -f environment.yml

Now there should be new Python environment titled mpathic_env. The environment can be activated by:

conda activate mpathic_env

And deactivated by:

conda deactivate

(conda activate and conda deactivate only work on conda 4.6 and later versions. For conda versions prior to 4.6, run:

• Windows: activate or deactivate
• Linux and macOS: source activate or source deactivate

)

If any commands are run from the command line, it needs to be done inside the created environment. To confirm that the environment is functional, run the following line after activating the new environment:

mpathic learn_model --help

Which verifies that the installation proceeded as expected. Running this command should populate the command terminal with a list of available functions.

Finally, to use this environment in a Jupyter notebook, a kernel needs to be created. Therefore, activate the environment and run the following line:

python -m ipykernel install --user --name mpathic_env --display-name "Python (mpathic)"

When opening a notebook from the RegSeq/notebooks folder, click on 'Kernel', 'Change Kernel', and select the newly-created kernel. You will now be able to import the package and execute the code.

You should be set up to use all code provided in this repository. If you encounter any issues with the installation, please contact us through GitHub.