ScreenR

DOI: 10.18129/B9.bioc.ScreenR  

Package to Perform High Throughput Biological Screening

Bioconductor version: Release (3.16)

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>

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("ScreenR")

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

Documentation

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

browseVignettes("ScreenR")

 

HTML	R Script	ScreenR Example Analysis
PDF		Reference Manual
Text		NEWS
Text		LICENSE

Details

biocViews	AssayDomain, GeneExpression, Software
Version	1.0.0
In Bioconductor since	BioC 3.16 (R-4.2) (< 6 months)
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)
LinkingTo
Suggests	rmarkdown (>= 2.11), knitr (>= 1.37), testthat (>= 3.0.0), BiocStyle(>= 2.22.0), covr (>= 3.5)
SystemRequirements
Enhances
URL	https://emanuelsoda.github.io/ScreenR/
BugReports	https://github.com/EmanuelSoda/ScreenR/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	ScreenR_1.0.0.tar.gz
Windows Binary	ScreenR_1.0.0.zip
macOS Binary (x86_64)	ScreenR_1.0.0.tgz
macOS Binary (arm64)	ScreenR_1.0.0.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/
Package Downloads Report	Download Stats