| ggcontrib {nadiv} | R Documentation |
Genetic group contribution
Description
Calculates the genomic contribution each genetic group makes to every individual in a pedigree
Usage
ggcontrib(pedigree, ggroups = NULL, fuzz = NULL, output = "matrix")
Arguments
pedigree |
A pedigree where the columns are ordered ID, Dam, Sire |
ggroups |
An optional vector of either: genetic group assignment for
every individual or just the unique genetic groups. |
fuzz |
A matrix containing the fuzzy classification of phantom parents
into genetic groups. |
output |
Format for the output |
Details
The specification of genetic groups is done in one of two approaches, either using fuzzy classification or not.
Fuzzy classification enables phantom parents to be assigned to (potentially)
more than one genetic group (Fikse 2009). This method requires unique
phantom parent identities to be included in the pedigree for all observed
individuals with unknown parents. For 'p' phantom parents, 'p' identities
should be listed as individuals in the first 'p' rows of the pedigree and
these should be the only individuals in the pedigree with missing values in
their Dam and Sire columns (denoted by either 'NA', '0', or '*'). The matrix
supplied to the fuzz argument should have 'p' rows (one for each
phantom parent) and 'r' columns, where 'r' is the number of genetic groups.
Non-fuzzy classification can handle the specification of genetic groups in three formats:
(1) similar to ASReml's format for specifying genetic groups, the first 'r'
rows of the pedigree (given to the pedigree argument) contain the
label for each genetic group in the ID column and indicate missing values
for the Dam and Sire columns (denoted by either 'NA', '0', or '*'). No
object is supplied to the ggroups argument. All individuals in the
pedigree must then have one of the 'r' genetic groups as parent(s) for each
unknown parent. Note, a warning message indicating In
numPed(pedigree): Dams appearing as Sires is expected, since the dam and
sire can be the same for all individuals in the pedigree composing the base
population of a genetic group.
(2) similar to Jarrod Hadfield's rbv function arguments in the
MCMCglmm package, for a pedigree of dimension i x 3 (given to the
pedigree argument), where 'i' is the total number of individuals in
the pedigree, a similar vector of length 'i' is given to the ggroups
argument. This vector lists either the genetic group to which each
individual's phantom parents belong or NA if the individual is not to be
considered part of one of the base populations (genetic groups). NOTE, this
approach does not allow phantom dams and phantom sires of a given individual
to be from different genetic groups.
(3) similar to DMU's format for specifying genetic groups. For a pedigree of
dimension i x 3 (given to the pedigree argument), where 'i' is the
total number of individuals in the pedigree, instead of missing values for a
parent, one of the 'r' genetic groups is specified. A character vector of
length 'r' with unique genetic group labels is given to the ggroups
argument. Note, that all individuals with a missing parent should have a
genetic group substituted instead of the missing value symbol (i.e., either
'NA', '0', or '*').
Value
Returns i x r genetic group contributions to all 'i' individuals
from each of the 'r' genetic groups. Default output is an object of class
matrix (dense), but this format can be changed (e.g., "dgCMatrix"
for a sparse matrix).
Author(s)
References
Fikse, F. 2009. Fuzzy classification of phantom parent groups in an animal model. Genetics, Selection, Evolution. 41:42.
Quaas, R.L. 1988. Additive genetic model with groups and relationships. Journal of Dairy Science. 71:1338-1345.
Examples
# Use the pedigree from Quaas 1988 (See `data(Q1988)`)
##########################
# Fuzzy classification
## Fuzzy classification with complete assignment to one group
Q1988fuzz <- Q1988[-c(1:2), c("id", "phantomDam", "phantomSire")]
Qfnull <- matrix(c(1,0,0,1,0, 0,1,1,0,1), nrow = 5, ncol = 2,
dimnames = list(letters[1:5], c("g1", "g2")))
(Qfuzznull <- ggcontrib(Q1988fuzz, fuzz = Qfnull))
## Should be identical to the non-fuzzy classification output
# format (1) from above
(Q <- ggcontrib(Q1988[-c(3:7), c(1,4,5)]))
stopifnot(Qfuzznull == Q)
## Fuzzy classification with arbitrary assignments
Qf <- matrix(c(1,0,0.5,0.5,0.5, 0,1,0.5,0.5,0.5), nrow = 5, ncol = 2,
dimnames = list(letters[1:5], c("g1", "g2")))
(Qfuzz <- ggcontrib(Q1988fuzz, fuzz = Qf))
## Using the pedigree and fuzzy classification in Fikse (2009)
F2009fuzz <- data.frame(id = c(letters[1:7], LETTERS[1:6]),
dam = c(rep(NA, 7), "a", "c", "e", "A", "C", "D"),
sire = c(rep(NA, 7), "b", "d", "f", "B", "g", "E"))
Ff <- matrix(c(1,0,1,0,0,0,0.2,
0,1,0,0.6,0,0.3,0.4,
0,0,0,0.4,1,0.7,0.4),
nrow = 7, ncol = 3,
dimnames = list(letters[1:7], paste0("g", 1:3)))
# Actual Q matrix printed in Fikse (2009)
Fikse2009Q <- matrix(c(0.5,0.5,0,0.5,0.1,0.3,
0.5,0.3,0.15,0.4,0.275,0.3375,
0,0.2,0.85,0.1,0.625,0.3625),
nrow = 6, ncol = 3,
dimnames = list(LETTERS[1:6], paste0("g", seq(3))))
Ffuzz <- ggcontrib(F2009fuzz, fuzz = Ff)
(diffFfuzz <- Ffuzz - Fikse2009Q)
# Encountering some rounding error
stopifnot(length((drop0(diffFfuzz, tol = 1e-12))@x) == 0)
##########################
# Non-fuzzy classification
# format (1) from above
Q1 <- Q1988[-c(3:7), c(1,4,5)]
(gg1 <- ggcontrib(Q1, ggroups = NULL)) # note the warning message which is typical
# format (2) from above
Q2 <- Q1988[-c(1:7), 1:3]
# arbitrarily assign individuals genetic groups for unknown parents
## Means gg2 is NOT comparable to gg1 or gg3!
ggvec.in <- c("g1", "g2", "g1", NA)
(gg2 <- ggcontrib(Q2, ggroups = ggvec.in))
# format (3) from above
Q3 <- Q1988[-c(1:7), c(1,4,5)]
gg3 <- ggcontrib(Q3, ggroups = c("g1", "g2"))
stopifnot(gg1 == gg3)