Lilace is an R package for scoring FACS-based DMS experiments with uncertainty quantification. It takes in a negative control group (usually synonymous variants) and scores each variant relative to the negative control group.
Installation
R package installation
Lilace relies on cmdstanr, which should be properly installed first.
install.packages("cmdstanr", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
# use cmdstanr to install CmdStan, this requires a working C++ toolchain and compiler
library(cmdstanr)
install_cmdstan(cores = 2)
The compiler requirements can be seen at stan-dev. If you run into issues with installation, please ensure your gcc version is > 5.
Then, install Lilace from GitHub.
if (!requireNamespace("remotes", quietly = TRUE)) {
install.packages("remotes")
}
remotes::install_github("pimentellab/lilace")
library(lilace)
Docker installation
If you prefer to use docker or run into issues with the regular installation, a docker image is available
To connect the container to an interactive command line environment run
To instead launch Rstudio in the container, you can specify a port and run
Then go to http://localhost:8888/ and use username “rstudio” and your input password to login. From there, you can call library(lilace)
and check that you can run the intro vignette code.
If you would like to build the container yourself or make adjustments, the Dockerfile is available and can be built with
How to use Lilace
An introductory vignette can be found here. If you run into any problems, please submit an issue on github or email jfreudenberg@ucla.edu.