Package: pmm 1.37.0
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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:
pmm_1.37.0.tar.gz
pmm_1.37.0.zip(r-4.5)pmm_1.37.0.zip(r-4.4)pmm_1.37.0.zip(r-4.3)
pmm_1.37.0.tgz(r-4.4-any)pmm_1.37.0.tgz(r-4.3-any)
pmm_1.37.0.tar.gz(r-4.5-noble)pmm_1.37.0.tar.gz(r-4.4-noble)
pmm_1.37.0.tgz(r-4.4-emscripten)pmm_1.37.0.tgz(r-4.3-emscripten)
pmm.pdf |pmm.html✨
pmm/json (API)
NEWS
# Install 'pmm' in R: |
install.packages('pmm', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- kinome - Example Data from InfectX
On BioConductor:pmm-1.37.0(bioc 3.20)pmm-1.36.0(bioc 3.19)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:0d59076414
Exports:hitheatmappmmsharedness
Dependencies:bootlatticelme4MASSMatrixminqanlmenloptrRcppRcppEigen
Readme and manuals
Help Manual
Help page | Topics |
---|---|
The PMM-Package | pmm-package |
Visualization of the PMM results | hitheatmap |
Example Data from InfectX | kinome |
Fitting the PMM | pmm |
Sharedness Score | sharedness |