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Lilace

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

docker pull jfreudenberg/lilace

To connect the container to an interactive command line environment run

docker container run -it lilace bash

To instead launch Rstudio in the container, you can specify a port and run

docker run -p 8888:8787 -e PASSWORD=<password> lilace

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

docker buildx build --platform linux/amd64,linux/arm64 --build-arg WHEN=2025-06-27 -t lilace .

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 .