Learn R Programming

noia (version 0.94.1)

Effects names: Names of Genetic Effects

Description

Provides and manipulates labels of genetic effects.

Usage

effectsNamesGeneral(nloc = 2, max.level=NULL, max.dom=NULL)	
effectsNamesMultilinear(nloc=2, max.level=2, max.dom=2)
statusMaxLevel(effect, max.level=NULL)
statusMaxDom(effect, max.dom=NULL)
effectsSelect(nloc, max.level=NULL, max.dom=NULL, effects=NULL)
effNames(effects=NULL, loci=NULL, nloc=1)

Arguments

nloc
Number of loci.
max.level
Maximum order of interactions.
max.dom
Maximum order for dominance.
effect
A string or characters representing a genetic effect.
effects
Vector of effects.
loci
Vector of loci.

Details

The codes for genetic effects are stored into a vector of length 4, effectsNames. The first element of the vector is the code for the absence of effect (default: "."). The three other elements are respectively additive effects (default: "a") dominance effects (default: "d"), and multilinear epistatic effects (default: "e"). The names of genetic effects contains as many characters as the number of loci in the system. The additive effect of the first locus in a 3-locus system will be "a..", and the "Dominance by Dominance" between loci 2 and 4 in a 5-locus system will be ".d.d.". Directionality of epistasis between two (or more) loci is indicated by as many "e" as necessary (e.g. ".ee." for the interaction between loci 2 and 3 in a 4-locus case).

effectsNamesGeneral and effectsNamesMultilinear provide a list of the names of the genetic effects, in the correct order to be processed in the NOIA framework (Alvarez-Castro and Carlborg 2007). effectsSelect returns a vector of effects matching the maximum levels. statusMaxLevel and statusMaxDom return TRUE if a given effect is under the level and dominance threshold, respectively. effNames is a low-level routine, called by the other functions. It provides names "on demand", for instance effNames(c("a","d"),c(2,4),5) will generate ".a.d.", i.e. an "a" at locus 2 and a "d" at locus 4, in a set of 5 loci.

References

Alvarez-Castro JM, Carlborg O. (2007). A unified model for functional and statistical epistasis and its application in quantitative trait loci analysis. Genetics 176(2):1151-1167. Le Rouzic A, Alvarez-Castro JM. (2008). Estimation of genetic effects and genotype-phenotype maps. Evolutionary Bioinformatics, 4.

See Also

geneticEffects, genNames, linearRegression, multilinearRegression.

Examples

Run this code
effectsNamesGeneral(3)
effectsSelect(nloc=3, max.level=1)

Run the code above in your browser using DataLab