replicates: Design a batch experiment with experimental controls

In experDesign: Design Experiments for Batches

Design a batch experiment with experimental controls

Description

To ensure that the batches are comparable some samples are processed in each batch. This function allows to take into account that effect. It uses the most different samples as controls as defined with extreme_cases().

Usage

replicates(pheno, size_subset, controls, omit = NULL, iterations = 500)

Arguments

pheno	Data.frame with the sample information.
size_subset	Numeric value of the number of sample per batch.
controls	The numeric value of the amount of technical controls per batch.
omit	Name of the columns of the pheno that will be omitted.
iterations	Numeric value of iterations that will be performed.

Details

To control for variance replicates are important, see for example https://www.nature.com/articles/nmeth.3091.

Value

A index with some samples duplicated in the batches.

See Also

design(), extreme_cases().

Examples

samples <- data.frame(L = letters[1:25], Age = rnorm(25),
                      type = sample(LETTERS[1:5], 25, TRUE))
index <- replicates(samples, 5, controls = 2, omit = "L", iterations = 10)
head(index)

experDesign documentation built on May 29, 2024, 9:20 a.m.