installation steps

1 - setup conda with R available

conda create -n -c conda-forge arion_r r-essentials r-base numpy pandas jupyterlab networkx python-levenshtein matplotlib sortedcontainers
conda activate arion_r
conda install -c conda-forge jupyterlab

2 - install the arion utilities into the environment

navigate to directory where setup.py is located (cd <cloned directory>) and run: pip install -e .

3 - install R

brew tap homebrew/science
brew install r

4 - Link R and jupyter kernels

Open R command line:

install.packages('IRkernel')
IRkernel::installspec(user = FALSE)

5 - Open jupyter lab

jupyter lab

6 - install R requirements Open the notebooks/speaq.R.ipynb notebook, uncomment the first cell and run!

repo description

• arion/: python package with utils for GISSMO lookups
• bin/scraper.py: download files from GISSMO
• bin/grid_search.py: run grid search to try to identify metabolites in a specific data set
• papers: relevant academic papers
• notebooks/speaq.R.ipynb: code provided by speaq developers for demonstration purposes
• notebooks/arion_speaq.R.ipynb: speaq library applied to arion data
• notebooks/correlation_analysis.ipynb: runs on the outputs of the R notebook to identify metabolites

Notes:

1- if opening one of the R kernels for the first time, you will need to switch the kernel to R from the default which is python. This can be done by clicking on the kernel on the top right hand side of the jupyter lab notebook.

2- To test that R is set up correctly open notebooks/speaq.R.ipynb and run through the commands.

R setup resources:

https://docs.anaconda.com/anaconda/user-guide/tasks/use-r-language/ https://irkernel.github.io/installation/ https://richpauloo.github.io/2018-05-16-Installing-the-R-kernel-in-Jupyter-Lab/