rosace

Update

v1.1: May 30, 2024

Added options to take out nonsense/stop mutations from position-level estimates
Fixed a bug in position-level lfsr computation
The latest version 1.1 is uploaded at docker image
cmdstanr is updated and the csv reading format is different from the past. We recommend the user to use cmdstan version 2.35.0 (default install built in the package) and cmdstanr version >= 0.8.0 to avoid the trouble. However, if there is a link error (see issue #6) with cmdstan 2.35.0 on linux system, downgrade the version to 2.33.1 by specifying option "cmdstan_ver" in "runRosace" function.

docker pull roseraosh/rosace:latest

Overview

rosace is an R package for analyzing growth-based deep mutational scanning screen data.

Installation

rosace uses cmdstanr to run inference. Please ensure that cmdstanr is properly installed before installing rosace. Below is a concise installation command; for complete details, please refer to the official website.

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 = 4)

To install rosace start R and first install devtools by typing

install.packages("devtools")

and install rosace by typing

devtools::install_github("pimentellab/rosace")

If you prefer to use Docker, we also provide a Docker image for rosace. You can pull the image in the command line with

docker pull cbmacdo/rosace-docker

More detailed instructions on docker image is provided in this repo.

See the full Installation Instructions for further details and alternative installation options.

Getting started

library("rosace")

We recommend starting with the vignette. A vignette for the simulation module Rosette is also avaliable.

Further help

You may submit a bug report here on GitHub as an issue or you could send an email to roserao@ucla.edu.

Citing rosace

Please cite the following publication if you use rosace: Rao, J., Xin, R., Macdonald, C. et al. Rosace: a robust deep mutational scanning analysis framework employing position and mean-variance shrinkage. Genome Biol 25, 138 (2024). https://doi.org/10.1186/s13059-024-03279-7