Bioconductor version: Release (3.6)
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")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("pmm")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("pmm")
R Script | User manual for R-Package PMM | |
Reference Manual | ||
Text | NEWS |
biocViews | Regression, Software, SystemsBiology |
Version | 1.10.0 |
In Bioconductor since | BioC 3.1 (R-3.2) (3 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 |
Follow Installation instructions to use this package in your R session.
Source Package | pmm_1.10.0.tar.gz |
Windows Binary | pmm_1.10.0.zip |
Mac OS X 10.11 (El Capitan) | pmm_1.10.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/pmm |
Package Short Url | http://bioconductor.org/packages/pmm/ |
Package Downloads Report | Download Stats |
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