| conditionCombination {designGG} | R Documentation |
Generate a matrix indicating all possible levels for environmental
factors with dimension nConditions $times$ nEnvFactors.
This is a subfunction needed for designScore, but is not directly used.
conditionCombination( nEnvFactors, nLevels, Level, envFactorNames )
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.
|
nLevels |
number of levels for each factor, a vector with each
component being integer. The length should be equal to
nEnvFactors.
|
Level |
a list which specifies the levels for each factor in the
experiment. There are in total nEnvFactors elements in the list and each
element correspsonds to certain envrironmental factor. The element is a
vector describing all levels of the environmental factor.
Default setting for the level of each factor is 1, 2, ...., nLevels[i]. (Here
nLevels[i] is the ith element of nLevels, which tells the total number of
levels for i environmental factor).
|
envFactorNames |
a vector with names for all environmental factor(s). For example, for an
experiment with two environmental factors of temperature and drug treatment:
envFactorNames <- c( "Temperature", "Dosage" ) Default = NULL, then the output will use "F1" and "F2" to indicate the
environmental factors.
|
Currently this function works only when nEnvFactors is between 1 and 3.
A matrix with dimension of nConditions $times$ nEnvFactors. Each element in the matrix indicates the levels of corresponding environmental factor.
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. (submitted)
http://gbic.biol.rug.nl/designGG