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

3.70 score 1 stars 3 scripts 226 downloads 3 exports 46 dependencies

Last updated 6 months agofrom:8e90812a1c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-winOKNov 05 2024
R-4.5-linuxOKNov 05 2024
R-4.4-winOKNov 05 2024
R-4.4-macOKNov 05 2024
R-4.3-winOKNov 05 2024
R-4.3-macOKNov 05 2024

Exports:adjust_batchdiagnose_modelsplot_batch

Dependencies:backportsbroomclicolorspacecpp11dplyrfansifarvergeepackgenericsggplot2gluegtableisobandlabelinglatticelifecyclelimmamagrittrMASSMatrixMatrixModelsmgcvmunsellnlmennetpillarpkgconfigpurrrquantregR6RColorBrewerrlangscalesSparseMstatmodstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

Get Started: Methods to address batch effects

Rendered frombatchtma.Rmdusingknitr::rmarkdownon Nov 05 2024.

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