updateDesign: Updates current design
In designGG: Computational tool for designing genetical genomics experiments.

Description Usage Arguments Details Value Author(s) References

Updates current experimental design (including array.allocation and condition.allocation).

1 2	updateDesign( array.allocation, condition.allocation, nRILs, nSlides, nEnvFactors, nTuple, bTwoColorArray )

`array.allocation`	matrix with nArray rows and nRIL columns. Elements of 1/0 indicate this RIL (or strain) is/not selected for this array.
`condition.allocation`	matrix with nCondition rows and nRIL columns. Elements of 1/0 indicate this RIL (or strain) is/not selected for this condition.
`nRILs`	number of RILs (or strains) available for the experiment.
`nSlides`	total number of slides available for experiment.
`nEnvFactors`	number of environmental factors, an integer bewteen 1 and 3. When `nEnvFactors` is 1 and the number of levels for the enviromental factor (`nLevels`)is 1, there is one condition in the experiment (i.e. no enviromental perturbation) and thus only genetic factor will be considered in the algorithm. When `nEnvFactors` is 1 and nLevels is larger than 1 or `nEnvFactors` is larger than 1, all main factor(s) and interacting facotr(s) will be included. Examples: If there is a temperature perturbation, then `nEnvFactors` is 1; If there is both temperature and drug treatment perturbation, then `nEnvFactors` is 2.
`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 show the message, `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

This function calls two subfunctions: conditionUpdate and arrayUpdate.

a list with two elements, array.allocation and condition.allocation.

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>

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

designGG documentation built on May 2, 2019, 5:51 a.m.