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This is the development version of ScreenR; for the stable release version, see ScreenR.

Package to Perform High Throughput Biological Screening

Bioconductor version: Development (3.19)

ScreenR is a package suitable to perform hit identification in loss of function High Throughput Biological Screenings performed using barcoded shRNA-based libraries. ScreenR combines the computing power of software such as edgeR with the simplicity of use of the Tidyverse metapackage. ScreenR executes a pipeline able to find candidate hits from barcode counts, and integrates a wide range of visualization modes for each step of the analysis.

Author: Emanuel Michele Soda [aut, cre] (0000-0002-2301-6465), Elena Ceccacci [aut] (0000-0002-2285-8994), Saverio Minucci [fnd, ths] (0000-0001-5678-536X)

Maintainer: Emanuel Michele Soda <emanuelsoda at gmail.com>

Citation (from within R, enter citation("ScreenR")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

ScreenR Example Analysis HTML R Script
Reference Manual PDF


biocViews AssayDomain, GeneExpression, Software
Version 1.5.0
In Bioconductor since BioC 3.16 (R-4.2) (1.5 years)
License MIT + file LICENSE
Depends R (>= 4.2)
Imports methods (>= 4.0), rlang (>= 0.4), stringr (>= 1.4), limma(>= 3.46), patchwork (>= 1.1), tibble (>= 3.1.6), scales (>= 1.1.1), ggvenn (>= 0.1.9), purrr (>= 0.3.4), ggplot2 (>= 3.3), stats, tidyr (>= 1.2), magrittr (>= 1.0), dplyr (>= 1.0), edgeR(>= 3.32), tidyselect (>= 1.1.2)
System Requirements
URL https://emanuelsoda.github.io/ScreenR/
Bug Reports https://github.com/EmanuelSoda/ScreenR/issues
See More
Suggests rmarkdown (>= 2.11), knitr (>= 1.37), testthat (>= 3.0.0), BiocStyle(>= 2.22.0), covr (>= 3.5)
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package ScreenR_1.5.0.tar.gz
Windows Binary ScreenR_1.5.0.zip
macOS Binary (x86_64) ScreenR_1.5.0.tgz
macOS Binary (arm64) ScreenR_1.5.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/ScreenR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/ScreenR
Bioc Package Browser https://code.bioconductor.org/browse/ScreenR/
Package Short Url https://bioconductor.org/packages/ScreenR/
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