geneFlowT {GeneticsPed} | R Documentation |
geneFlowT
and geneFlowTinv
creates gene flow matrix (T)
and its inverse (Tinv), while gameteFlowM
creates gamete flow
matrix (M). mendelianSamplingD
creates a mendelian sampling
covariance matrix (D).
geneFlowT(x, sort=TRUE, names=TRUE, ...) geneFlowTinv(x, sort=TRUE, names=TRUE, ...) gameteFlowM(x, sort=TRUE, names=TRUE, ...) mendelianSamplingD(x, matrix=TRUE, names=TRUE, ...)
x |
Pedigree |
sort |
logical, for the computation the pedigree needs to be sorted, but results are sorted back to original sorting (sort=TRUE) or not (sort=FALSE) |
names |
logical, should returned matrix have row/colnames; this can be used to get leaner matrix |
matrix |
logical, should returned value be a diagonal matrix or a vector |
... |
arguments for other methods |
geneFlowT
returns a matrix with coefficients that show the flow
of genes from one generation to the next one etc. geneFlowTinv
is
simply the inverse of geneFlowT
, but calculated as I - M,
where M is gamete flow matrix with coefficients that represent
parent gamete contribution to their offspring. mendelianSamplingD
is another matrix (D) for construction of relationship additive
matrix via decomposition i.e. A=TDT' (Henderson, 1976). Mrode
(2005) has a very nice introduction to these concepts.
Take care with sort=FALSE, names=FALSE
. It is your own
responsibility to assure proper handling in this case.
Matrices of n * n dimension, with coeficients as described in the
details, where n is number of subjects in x
Gregor Gorjanc
Henderson, C. R. (1976) A simple method for computing the inverse of a numerator relationship matrix used in prediction of breeding values. Biometrics 32(1):69-83
Mrode, R. A. (2005) Linear models for the prediction of animal breeding values. 2nd edition. CAB International. ISBN 0-85199-000-2 http://www.amazon.com/gp/product/0851990002
Pedigree
, relationshipAdditive
,
kinship
and inbreeding
data(Mrode2.1) Mrode2.1$dtB <- as.Date(Mrode2.1$dtB) x2.1 <- Pedigree(x=Mrode2.1, subject="sub", ascendant=c("fat", "mot"), ascendantSex=c("M", "F"), family="fam", sex="sex", generation="gen", dtBirth="dtB") fractions(geneFlowT(x2.1)) fractions(geneFlowTinv(x2.1)) fractions(gameteFlowM(x2.1)) mendelianSamplingD(x2.1)