Package: ARRmNormalization 1.47.0
Jean-Philippe Fortin
ARRmNormalization: Adaptive Robust Regression normalization for Illumina methylation data
Perform the Adaptive Robust Regression method (ARRm) for the normalization of methylation data from the Illumina Infinium HumanMethylation 450k assay.
Authors:
ARRmNormalization_1.47.0.tar.gz
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ARRmNormalization.pdf |ARRmNormalization.html✨
ARRmNormalization/json (API)
| # Install 'ARRmNormalization' in R: |
| install.packages('ARRmNormalization', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- ProbesType - Probe Design information for the 450k methylation assay
On BioConductor:ARRmNormalization-1.45.0(bioc 3.20)ARRmNormalization-1.44.0(bioc 3.19)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
dnamethylationtwochannelpreprocessingmicroarray
Last updated 23 days agofrom:528145733e. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 30 2024 |
| R-4.5-win | NOTE | Oct 30 2024 |
| R-4.5-linux | NOTE | Oct 30 2024 |
| R-4.4-win | NOTE | Oct 30 2024 |
| R-4.4-mac | NOTE | Oct 30 2024 |
| R-4.3-win | NOTE | Oct 30 2024 |
| R-4.3-mac | NOTE | Oct 30 2024 |
Exports:getBackgroundgetCoefficientsgetDesignInfogetQuantilesnormalizeARRmpositionPlotsquantilePlots
Dependencies:ARRmData
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| ARRm normalization for Illumina methylation data | ARRmNormalization-package ARRmNormalization |
| Estimate background intensity from the negative control probes | getBackground |
| Return the coefficients from the ARRm linear model | getCoefficients |
| Build the chip and position indices | getDesignInfo |
| Return the percentiles of a betaMatrix for each probe type | getQuantiles |
| Perform ARRm normalization | normalizeARRm |
| Plots to evalue chip position effects on different percentiles | positionPlots |
| Probe Design information for the 450k methylation assay | ProbesType |
| Diagnostic plots for evaluation of background effects and dye bias effects on different percentiles | quantilePlots |