prada

DOI: 10.18129/B9.bioc.prada    

This package is for version 3.7 of Bioconductor; for the stable, up-to-date release version, see prada.

Data analysis for cell-based functional assays

Bioconductor version: 3.7

Tools for analysing and navigating data from high-throughput phenotyping experiments based on cellular assays and fluorescent detection (flow cytometry (FACS), high-content screening microscopy).

Author: Florian Hahne <florian.hahne at novartis.com>, Wolfgang Huber <huber at ebi.ac.uk>, Markus Ruschhaupt, Joern Toedling <toedling at ebi.ac.uk>, Joseph Barry <joseph.barry at embl.de>

Maintainer: Florian Hahne <florian.hahne at novartis.com>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("prada")

Documentation

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

browseVignettes("prada")

 

PDF	R Script	Combining prada output and cellHTS2
PDF	R Script	Removal of contaminants from FACS data
PDF		Reference Manual

Details

biocViews	CellBasedAssays, Software, Visualization
Version	1.56.0
In Bioconductor since	BioC 1.6 (R-2.1) or earlier (> 13.5 years)
License	LGPL
Depends	R (>= 2.10), Biobase, RColorBrewer, grid, methods, rrcov
Imports	Biobase, BiocGenerics, graphics, grDevices, grid, MASS, methods, RColorBrewer, rrcov, stats4, utils
LinkingTo
Suggests	cellHTS2, tcltk
SystemRequirements
Enhances
URL
Depends On Me	facsDorit, RNAither
Imports Me	cellHTS2
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	prada_1.56.0.tar.gz
Windows Binary	prada_1.56.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan)	prada_1.56.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/prada
Source Repository (Developer Access)	git clone [email protected]:packages/prada
Package Short Url	http://bioconductor.org/packages/prada/
Package Downloads Report	Download Stats