Genetic effects {noia} | R Documentation |
geneticEffects
displays the genetic effects (and their standard
errors) from the result of linearRegression
. If a new
reference point is provided, a "change of reference" operation is performed
(Alvarez-Castro and Carlborg 2007).
effectsPvalues
and effectsVariances
display respectively
the P-value (probability for the effect to be = 0) and the part of
genetic variance due to this effect.
geneticEffects(obj, reference="P1", ref.genotype = NULL) effectsVariances(obj) effectsPvalues(reg)
obj |
An object of class "noia.linear" provided by
linearRegression . |
reference |
The new reference point. Can
be "F2" , "F1" , "Finf" , "P1" , "P2" (see
linearRegression for details. |
ref.genotype |
The same as reference , provided for compatibility
with older versions. |
reg |
Output of a regression (object of class "lm " or
"nls "). |
The P-values can be extracted from both linear and multilinear regressions. However, variance decomposition and change of reference operation are not possible from the result of a multilinear regression.
Arnaud Le Rouzic <a.p.s.lerouzic@bio.uio.no>
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.
linearRegression
, multilinearRegression
.
map <- c(0.25, -0.75, -0.75, -0.75, 2.25, 2.25, -0.75, 2.25, 2.25) pop <- simulatePop(map, N=500, sigmaE=0.2, type="F2") # Regressions linear <- linearRegression(phen=pop$phen, gen=cbind(pop$Loc1, pop$Loc2)) geneticEffects(linear, "P1") effectsVariances(linear)