Package: batchtma 0.1.7

Konrad Stopsack

batchtma: Batch Effect Adjustments

Different adjustment methods for batch effects in biomarker data, such as from tissue microarrays. Some methods attempt to retain differences between batches that may be due to between-batch differences in "biological" factors that influence biomarker values.

Authors:Konrad Stopsack [aut, cre], Travis Gerke [aut]

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batchtma.pdf |batchtma.html
batchtma/json (API)

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

Peer review:

Bug tracker:https://github.com/stopsack/batchtma/issues

On CRAN:

batch-effectsmeasurement-errortissue-microarray-analysis

3 exports 1 stars 1.02 score 46 dependencies 3 scripts 273 downloads

Last updated 3 months agofrom:8e90812a1c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 06 2024
R-4.5-winOKSep 06 2024
R-4.5-linuxOKSep 06 2024
R-4.4-winOKSep 06 2024
R-4.4-macOKSep 06 2024
R-4.3-winOKSep 06 2024
R-4.3-macOKSep 06 2024

Exports:adjust_batchdiagnose_modelsplot_batch

Dependencies:backportsbroomclicolorspacecpp11dplyrfansifarvergeepackgenericsggplot2gluegtableisobandlabelinglatticelifecyclelimmamagrittrMASSMatrixMatrixModelsmgcvmunsellnlmennetpillarpkgconfigpurrrquantregR6RColorBrewerrlangscalesSparseMstatmodstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

Get Started: Methods to address batch effects

Rendered frombatchtma.Rmdusingknitr::rmarkdownon Sep 06 2024.

Last update: 2023-02-16
Started: 2020-11-02