To install this package, start R and enter:

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

In most cases, you don't need to download the package archive at all.

pmm

   

This package is for version 3.3 of Bioconductor; for the stable, up-to-date release version, see pmm.

Parallel Mixed Model

Bioconductor version: 3.3

The Parallel Mixed Model (PMM) approach is suitable for hit selection and cross-comparison of RNAi screens generated in experiments that are performed in parallel under several conditions. For example, we could think of the measurements or readouts from cells under RNAi knock-down, which are infected with several pathogens or which are grown from different cell lines.

Author: Anna Drewek

Maintainer: Anna Drewek <adrewek at stat.math.ethz.ch>

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

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("pmm")

 

PDF R Script User manual for R-Package PMM
PDF   Reference Manual
Text   NEWS

Details

biocViews Regression, Software, SystemsBiology
Version 1.4.0
In Bioconductor since BioC 3.1 (R-3.2) (1.5 years)
License GPL-3
Depends R (>= 2.10)
Imports lme4, splines
LinkingTo
Suggests
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source pmm_1.4.0.tar.gz
Windows Binary pmm_1.4.0.zip
Mac OS X 10.9 (Mavericks) pmm_1.4.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/pmm/tree/release-3.3
Package Short Url http://bioconductor.org/packages/pmm/
Package Downloads Report Download Stats

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