Initialize an experiment design matrix

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Description

Allocate RILs (or strains) into different conditional and pair RILs (or strains) into slides.

Usage

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  initialDesign( genotype, nRILs, nSlides, nConditions, nTuple, 
                 bTwoColorArray )

Arguments

genotype

genotype data: a nMarker-by-nRILs matrix with two allels being 0 and 1 (or A and B) or three allels being 0, 0.5 and 1 (or, A, H, and B), where 0.5 (or H) represents heterozygous allele.

nRILs

total number of RILs ((or strains) available for the experiment.

nSlides

total number of slides available for the experiment.

nConditions

number of all possible combination of all environmental factors.

nTuple

average number of RILs (or strains) to be assigned onto each condition
nTuple should be a real number which is larger than 1.
if nTuple < 1, the algorithm will stop and shw the message below,
warning: "The number of slides is too small to perform the experiment."

bTwoColorArray

binary variable indicating experiment type:
bTwoColorArray <- TRUE \#for dual channel experiment
bTwoColorArray <- FALSE \#for single channel experiment

Details

For two-color array experiments, randomly choose a RIL (or strain) and pair it with the genetically most different RIL (or strain) on one array.
For one-color array experiments, array.allocation is NULL as there is no need to pair samples.

Value

a list with 2 matrices:
condition.allocation: allocate RILs (or strains) into different conditional (nCondition * nRILs)
array.allocation: pair RILs (or strains) into sldies (nSlides * nRILs)

Note

This function calls conditionAllocation function to allocate selected RILs (or strains) into different conditions.

Author(s)

Yang Li <yang.li@rug.nl>, Gonzalo Vera <gonzalo.vera.rodriguez@gmail.com>
Rainer Breitling <r.breitling@rug.nl>, Ritsert Jansen <r.c.jansen@rug.nl>

References

Y. Li, R. Breitling and R.C. Jansen. Generalizing genetical genomics: the added value from environmental perturbation, Trends Genet (2008) 24:518-524.
Y. Li, M. Swertz, G. Vera, J. Fu, R. Breitling, and R.C. Jansen. designGG: An R-package and Web tool for the optimal design of genetical genomics experiments. BMC Bioinformatics 10:188(2009)
http://gbic.biol.rug.nl/designGG

See Also

designGG

Examples

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library(designGG)
data(genotype)
nRILs <-100
nEnvFactors <- 2  
nConditions <-2
nLevels <- c( 2, 2 )
levels <- list ( c(16, 24), c(5, 10) )
nSlides <- 100
nTuple <- 25  
bTwoColorArray <- TRUE 
initialDesign( genotype, nRILs, nSlides, nConditions, nTuple, bTwoColorArray )