CRAN/E | designit

designit

Blocking and Randomization for Experimental Design

Installation

About

Intelligently assign samples to batches in order to reduce batch effects. Batch effects can have a significant impact on data analysis, especially when the assignment of samples to batches coincides with the contrast groups being studied. By defining a batch container and a scoring function that reflects the contrasts, this package allows users to assign samples in a way that minimizes the potential impact of batch effects on the comparison of interest. Among other functionality, we provide an implementation for OSAT score by Yan et al. (2012, doi:10.1186/1471-2164-13-689).

bedapub.github.io/designit/
github.com/BEDApub/designit/
Bug report File report

Key Metrics

Version 0.5.0
R ≥ 4.1.0
Published 2024-03-21 43 days ago
Needs compilation? no
License MIT
License File
CRAN checks designit results

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Maintainer

Maintainer

Iakov I. Davydov

iakov.davydov@roche.com

Authors

Iakov I. Davydov

aut / cre / cph

Juliane Siebourg-Polster

aut / cph

Guido Steiner

aut / cph

Konrad Rudolph

ctb

Jitao David Zhang

aut / cph

Balazs Banfai

aut / cph

F. Hoffman-La Roche

cph / fnd

Material

README
NEWS
Reference manual
Package source

Vignettes

Basic example
Using custom shuffle schedule
In-vivo study design
designit: a flexible engine to generate experiment layouts
Nested dimension example
Optimizer examples
OSAT and scoring functions
Plate layouts
Shuffling with constraints

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 4.1.0

Imports

rlang ≥ 0.4.0
dplyr ≥ 1.0.0
purrr
ggplot2
scales
tibble
tidyr
assertthat
stringr
R6
data.table
stats

Suggests

testthat
roxygen2
pkgdown
knitr
markdown
rmarkdown
gt
bench
OSAT
tidyverse
printr
devtools ≥ 2.0.0
ggpattern
cowplot
bestNormalize
here