conditionLevel {designGG} R Documentation

## Levels of all environmental factors

### Description

Describe the levels of all environmental factors for each RIL/strain in the experiment.
This is a subfunction needed for designScore, but is not directly used.

### Usage

    conditionLevel( array.allocation, condition.allocation,
condition.combination,nEnvFactors )


### Arguments

 array.allocation a matrix with nArray rows and nRIL columns. Elements of 1/0 indicates this RIL (or strain) is/not selected for this array. condition.allocation a matrix with nCondition rows and nRIL columns. Elements of 1/0 indicates this RIL (or strain) is/not selected for this condition. condition.combination a matrix indicating all possible levels for environmental factors, with dimension of nConditions by nEnvFactors. nEnvFactors number of environmental factors, an integer bewteen 1 and 3. When nEnvFactors is 1 and 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.

### Details

For single-channel experiment, array.allocation is NULL. Then the conditionLevel is decided by condition.allocation. For dual-channel experiment, array.allocation decides which RILs are selected and then the condition.allocation indicates which condition this RIL will be put in for the experiment.

### Value

A matrix with dimension of nRILs by nEnvFactors, each element indicates the level of a certain environmental factor to which the RIL (or strain) is exposed in the experiment.

### 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

designScore, conditionCombination