High-Throughput RNA-seq model fit
Why use HTRfit
HTRfit provides a robust statistical framework that allows you to investigate the essential experimental parameters influencing your ability to detect expression changes. Whether you're examining sequencing depth, the number of replicates, or other critical factors, HTRfit's computational simulation is your go-to solution.
Furthermore, by enabling the inclusion of fixed effects, mixed effects, and interactions in your RNAseq data analysis, HTRfit provides the flexibility needed to conduct your differential expression analysis effectively. HTRfit is particularly adapted for the analysis of large number of samples, or highly multiplexed experiments.
Installation
method A:
To install the latest version of HTRfit, run the following in your R console :
if (!requireNamespace("remotes", quietly = TRUE))
install.packages("remotes")
remotes::install_git("https://gitbio.ens-lyon.fr/aduvermy/HTRfit")method B:
You also have the option to download a release directly from the HTRfit release page. Once you've downloaded the release, simply launch following command.
## -- Example using the HTRfit-v2.0.0 release
install.packages('HTRfit-v2.0.0.tar.gz', repos = NULL, type='source')
When dependencies are met, installation should take a few minutes.
CRAN packages dependencies
The following depandencies are required:
## -- required
install.packages(c('parallel', 'data.table', 'ggplot2', 'gridExtra',
'glmmTMB', 'magrittr', 'MASS', 'reshape2',
'rlang', 'stats', 'utils', 'BiocManager', 'car'))
BiocManager::install('S4Vectors', update = FALSE)
## -- optional
BiocManager::install('DESeq2', update = FALSE)Docker
We have developed Docker images to simplify the package's utilization.
docker pull ruanad/htrfit:v2.0.0-beta
docker run -it --rm ruanad/htrfit:v2.0.0-betaHTRfit allows building graphs to visualize results. Inside Docker, displaying a window from the R terminal can be tricky and requires specific settings before running the container. Following commands worked for us:
# Prepare target env
CONTAINER_DISPLAY="0"
CONTAINER_HOSTNAME="htrfit_user"
# Create a directory for the socket
mkdir -p display/socket
touch display/Xauthority
# Get the DISPLAY slot
DISPLAY_NUMBER=$(echo $DISPLAY | cut -d. -f1 | cut -d: -f2)
# Extract current authentication cookie
AUTH_COOKIE=$(xauth list | grep "^$(hostname)/unix:${DISPLAY_NUMBER} " | awk '{print $3}')
# Create the new X Authority file
xauth -f display/Xauthority add ${CONTAINER_HOSTNAME}/unix:${CONTAINER_DISPLAY} MIT-MAGIC-COOKIE-1 ${AUTH_COOKIE}
# Proxy with the :0 DISPLAY
socat UNIX-LISTEN:display/socket/X${CONTAINER_DISPLAY},fork TCP4:localhost:60${DISPLAY_NUMBER} &
# Launch the container
docker run -it --rm \
-e DISPLAY=:${CONTAINER_DISPLAY} \
-e XAUTHORITY=/tmp/.Xauthority \
-v ${PWD}/display/socket:/tmp/.X11-unix \
-v ${PWD}/display/Xauthority:/tmp/.Xauthority \
--hostname ${CONTAINER_HOSTNAME} \
ruanad/htrfit:v2.0.0-beta
## inspired by : https://blog.yadutaf.fr/2017/09/10/running-a-graphical-app-in-a-docker-container-on-a-remote-server/Biosphere virtual machine
A straightforward way to use HTRfit is to run it on a Virtual Machine (VM) through Biosphere. We recommend utilizing a VM that includes RStudio for an integrated development environment (IDE) experience. Biosphere VM resources can also be scaled according to your simulation needs.
HTRfit can be installed using the method A.