Package: pmm 1.45.0

Anna Drewek

pmm: Parallel Mixed Model

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.

Authors:Anna Drewek

pmm_1.45.0.tar.gz
pmm_1.45.0.zip(r-4.7)pmm_1.45.0.zip(r-4.6)pmm_1.45.0.zip(r-4.5)
pmm_1.45.0.tgz(r-4.6-any)pmm_1.45.0.tgz(r-4.5-any)
pmm_1.45.0.tar.gz(r-4.7-any)pmm_1.45.0.tar.gz(r-4.6-any)
pmm_1.45.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
pmm/json (API)

# Install 'pmm' in R:

install.packages('pmm', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

kinome - Example Data from InfectX

On BioConductor:pmm-1.45.0(bioc 3.24)pmm-1.44.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

systemsbiology regression

4.15 score 5 scripts 300 downloads 7 mentions 3 exports 13 dependencies

Last updated from:c2c84893c6. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	151
linux-devel-x86_64	NOTE	215
source / vignettes	OK	203
linux-release-x86_64	NOTE	227
macos-release-arm64	NOTE	113
macos-oldrel-arm64	NOTE	99
windows-devel	NOTE	104
windows-release	NOTE	107
windows-oldrel	NOTE	106
wasm-release	OK	113