https://github.com/elliothershberg/scg-setup
https://github.com/elliothershberg/scg-setup
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/elliothershberg/scg-setup
- Owner: elliothershberg
- Created: 2022-03-10T05:57:24.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2022-03-10T05:57:26.000Z (over 3 years ago)
- Last Synced: 2025-01-09T17:37:04.324Z (5 months ago)
- Size: 1000 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# SCG Setup
## Overview
I had a lot of frustration using the [Stanford SCG Informatics Cluster](https://login.scg.stanford.edu/).
In particular, I was using OnDemand, which lets you start up an interactive RStudio Server connected to an interactive job.
It sounds great, but in practice had a lot of issues.
The RStudio version is out of date, and the graphics didn't work right.
The terminal and Git features were incredibly slow and would crash.
I had to pick all my settings each time I logged on.
Installing packages was a big headache using the R module on the server.
I decided it was too much of a drag on productivity.
Now I use a setup with VS Code and Anaconda.
## Setup
I use VS Code locally, with two critical extensions:
- Remote SSH: a Microsoft supported extension for remote development through an SSH connection. Amazing stuff
- vscode-R: an amazing extension for R language features. Requires `jsonlite`, `rlang`, and `languageserver` R packages.
I then use Conda for managing R environment and packages.
Some important steps:
- Downloaded miniconda for linux
- Downloaded `mamba` which is a much faster drop-in replacement for conda
- Had issues until I did a clean install from a YAML file with all dependencies listed using mamba.
Key conda channels are `conda-forge` and `bioconda`.
An important gotcha is that you have to set the `r.term.linux` and `r.path.linux` to the path of the R binary for the conda environment.
For example, `/home/hershe/miniconda3/envs/R_mesa_gxe/bin/R`