Package: rBiasCorrection 0.3.6

rBiasCorrection: Correct Bias in DNA Methylation Analyses

Implementation of the algorithms (with minor modifications) to correct bias in quantitative DNA methylation analyses as described by Moskalev et al. (2011) <doi:10.1093/nar/gkr213>. Publication: Kapsner et al. (2021) <doi:10.1002/ijc.33681>.

Authors:Lorenz A. Kapsner [cre, aut, cph], Evgeny A. Moskalev [aut]

rBiasCorrection_0.3.6.tar.gz
rBiasCorrection_0.3.6.zip(r-4.7)rBiasCorrection_0.3.6.zip(r-4.6)rBiasCorrection_0.3.6.zip(r-4.5)
rBiasCorrection_0.3.6.tgz(r-4.6-any)rBiasCorrection_0.3.6.tgz(r-4.5-any)
rBiasCorrection_0.3.6.tar.gz(r-4.7-any)rBiasCorrection_0.3.6.tar.gz(r-4.6-any)
rBiasCorrection_0.3.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
rBiasCorrection/json (API)

# Install 'rBiasCorrection' in R:
install.packages('rBiasCorrection', repos = c('https://kapsner.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kapsner/rbiascorrection/issues

Datasets:

On CRAN:

Conda:

bias-correctiongene-methylationpcrquarto

4.78 score 1 stars 1 packages 9 scripts 843 downloads 17 exports 29 dependencies

Last updated from:1a9feeaee9. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK557
source / vignettesOK212
linux-release-x86_64OK371
macos-release-arm64OK237
macos-oldrel-arm64OK316
windows-develOK352
windows-releaseOK360
windows-oldrelOK336
wasm-releaseOK162

Exports:aggregated_inputbetter_modelbiascorrectionclean_dtclean_upcreate_exampleplotcreatebarerrorplotsget_timestamphandle_text_inputon_startplotting_utilityregression_utilitysolving_equationsstatistics_listsubstitutions_createwrite_csvwrite_log

Dependencies:clicodetoolscpp11data.tabledigestfarverfuturefuture.applyggplot2globalsgluegtableisobandlabelinglifecyclelistenvminpack.lmnls2parallellypolynomprotoR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

rBiasCorrection_enchmarking
Available Cores | Benchmarking

Last update: 2026-02-01
Started: 2025-04-05

rBiasCorrection_howto
Introduction | Setup the prerequisites | Conduct the correction of experimental biases | Background information | General regression equations | Data dependent regression equations (experimental feature) | Selection of the correction algorithm | Outputs and Results | Regression plots

Last update: 2025-04-05
Started: 2025-04-05