Installation from source
NOTE: For Sanger farm22 users see instructions below
This will install the latest development version. These docs are for tglow-r v0.1.23 or later. The only tagged release (v0.1.2) is older than this, so for stability you can install a specific commit with the ref argument of remotes::install_git(), for example ref = "<commit sha>".
If you need to build some dependencies from source, make sure there is a BLAS/LAPACK, nlopt (nlopt), libxml2 (igraph) lib available if it isn't already, otherwise dependencies likely will not install. However this will depend heavily on your setup. Below is a minimal example using conda.
arrow is needed to read the parquet files of tglow-pipeline v0.2.0. On Linux, installing it from CRAN can mean building it from source, so installing r-arrow with conda (or install.packages("arrow") before tglow-r) is usually easier.
Then launch R
This unlocks all of the core functionality
Installing suggested packages
There are several suggested packages that enable additional functionality relating to visualizing images. These are outlined below.
ggrastr - Rasterizing large plots
To enable rasterization of plots with many points (this is fully optional, and plotting will work without it)
Then launch R
EBImage and ggiraph - Visualizing cells and Interactive plots
To enable visualizing images and making interactive plots EBImage, hdf5r, png, base64enc and ggiraph packages are required
For detailed install instructions for ggiraph see: https://davidgohel.github.io/ggiraph/
Installing on Sanger farm22 - latest dev version
A version compatible with the tglow-r softpack module comes pre-installed in /software/teamtrynka/installs/tglow-rlibs and can be loaded as such.
Option 1: Using pre-installed version (recommended)
NOTE: The version here changes often at the moment, so might not be the most stable.
Then launch R.
Option 2: Installing into your personal library from git
Alternatively you can install if using R from the headnode or jammy64 directly from GitHub. This module should have all dependencies pre-installed.
Then launch R.