pmm

Parallel Mixed Model

Bioconductor version: Release (3.20)

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 (version "4.4") and enter:


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

BiocManager::install("pmm")

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("pmm")

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

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Regression, Software, SystemsBiology
Version	1.38.0
In Bioconductor since	BioC 3.1 (R-3.2) (9.5 years)
License	GPL-3
Depends	R (>= 2.10)
Imports	lme4, splines
System Requirements
URL

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Build Report	Build Report

Package Archives

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

Source Package	pmm_1.38.0.tar.gz
Windows Binary (x86_64)	pmm_1.38.0.zip (64-bit only)
macOS Binary (x86_64)	pmm_1.38.0.tgz
macOS Binary (arm64)	pmm_1.37.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/pmm
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/pmm
Bioc Package Browser	https://code.bioconductor.org/browse/pmm/
Package Short Url	https://bioconductor.org/packages/pmm/
Package Downloads Report	Download Stats