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https://github.com/cossio/samapp2024.jl

Code for the SAM-I riboswitch paper
https://github.com/cossio/samapp2024.jl

Last synced: 10 days ago
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Code for the SAM-I riboswitch paper

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README 

        
This repository hosts the source code for the paper:



> *Designing Molecular RNA Switches with Restricted Boltzmann Machines*

> 

> by Jorge Fernandez-de-Cossio-Diaz, Pierre Hardouin, Francois-Xavier Lyonnet du Moutier, Andrea Di Gioacchino, Bertrand Marchand, Yann Ponty, Bruno Sargueil, Rémi Monasson, Simona Cocco

> 

> bioRxiv preprint: https://www.biorxiv.org/content/10.1101/2023.05.10.540155v2.abstract



If you use this code, please cite this paper (or you can use the included [CITATION.bib](https://github.com/cossio/SamApp2024.jl/blob/main/CITATION.bib)).



# Setup



The code is organized as a [Julia](https://julialang.org) package. If you haven't setup Julia on your computer, you can install it following the simple instructions from the [official website](https://julialang.org/downloads/). We have tested our package on the latest Julia version at the time of writing (`v1.10.4`). It should work on future non-breaking versions (`v1.x.y`) of Julia as well.



After having installed Julia, clone this repository locally using `git`, on a local directory, by running the following command from the terminal:



```bash

git clone https://github.com/cossio/SamApp2024.jl.git

```



Then, navigate to this directory in your terminal, start Julia (by running `julia` in the terminal), and then activate the included `Project.toml` by running the command:



```julia

julia> import Pkg

julia> Pkg.activate(pwd()) # activate the project in the current directory

julia> Pkg.instantiate() # install all the dependencies

```



The last command will install all the dependencies of this package.



Next, we will configure storage for downloading data from Rfam. Create a file named `LocalPreferences.toml` in the root directory of this package, and add the following lines:



```toml

[Rfam]

RFAM_DIR = "[path to local Rfam directory]"

RFAM_VERSION = "14.7"

```



where `[path to local Rfam directory]` should be replaced with the path to some local directory of your choosing, where the package will place data downloaded from Rfam.



Lastly, import the package within a Julia session by running:



```julia

julia> import SamApp2024

```



You can use this command in the Julia REPL. The first time you import it, it might some time for precompilation (but future imports should be faster).



At this point you can call any of the functions in the package.



## Running the Pluto notebooks



The included [Pluto notebooks](https://github.com/cossio/SamApp2024.jl/tree/main/pluto) contain the code for the downstream analysis done in the paper (which depend on the `SamApp2024` package). For more information about Pluto notebooks, see: https://plutojl.org.



To setup Pluto, start a fresh Julia session, and then run the following commands:



```julia

julia> import Pkg

julia> Pkg.add("Pluto")

julia> import Pluto; Pluto.run()

```



This starts a Pluto server. Now open your browser, and navigate to `localhost:1234`, which is the default address where Pluto is listening. You can then open the notebooks by navigating to the `pluto` directory in the repository, and opening the `.jl` files.



# Related packages 



The code implementing Restricted Boltzmann machines (training, sampling, and other functions) is provided in a separate package: https://github.com/cossio/RestrictedBoltzmannMachines.jl. Note that this package will be installed automatically as a dependency of this repository by the Julia package manager.



The code for simulations of other riboswitch families (reported in Supplementary Materials of the paper cited above) can be found at the following repository: https://github.com/cossio/RiboswitchesSimulations20240620.jl.



It is also possible to execute the Jupyter notebooks in Google Colab, see https://colab.research.google.com/github/ageron/julia_notebooks/blob/master/Julia_Colab_Notebook_Template.ipynb for an example.



For an alternative implementation of Restricted Boltzmann machines in Python, see https://github.com/jertubiana/PGM. In particular, we have prepared a repository at https://github.com/cossio/SamApp2024Py, showing how to use this Python package to train an RBM on RNA sequences from the RF00162 family.



# Issues



If you encounter any problems, or need help setting up this package, please [open an issue](https://github.com/cossio/SamApp2024.jl/issues/new/choose) in this repository.