knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
ScreenR is an easy and effective package to perform hits identification in loss of function High Throughput Biological Screening performed with shRNAs library. ScreenR combines the power of software like edgeR with the simplicity of the Tidyverse metapackage. ScreenR executes a pipeline able to find candidate hits from barcode counts data and integrates a wide range of visualization for each step of the analysis
Get the latest stable R
release from CRAN note
that you need to have R 4.3
or greater to use ScreenR
. Then install
ScreenR
from Bioconductor using the following code:
if (!requireNamespace("BiocManager", quietly = TRUE)) { install.packages("BiocManager") } BiocManager::install("ScreenR")
And the development version from GitHub with:
devtools::install_github("EmanuelSoda/ScreenR")
Please note that the ScreenR
was only made possible thanks to many other R and bioinformatics software authors, which are cited either in the vignettes and/or the paper(s) describing this package.
Below is the citation output from using citation('ScreenR')
in R
. Please run this yourself to check for any updates on how to cite ScreenR.
print(citation('ScreenR'))
Please note that the ScreenR
project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
r BiocStyle::CRANpkg('usethis')
, r BiocStyle::CRANpkg('remotes')
, and r BiocStyle::CRANpkg('rcmdcheck')
customized to use Bioconductor's docker containers and r BiocStyle::Biocpkg('BiocCheck')
.r BiocStyle::CRANpkg('covr')
.r BiocStyle::CRANpkg('pkgdown')
.r BiocStyle::CRANpkg('styler')
.r BiocStyle::CRANpkg('devtools')
and r BiocStyle::CRANpkg('roxygen2')
.For more details, check the dev
directory.
This package was developed using r BiocStyle::Biocpkg('biocthis')
.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.