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### TDT.R
###------------------------------------------------------------------------
### What: Gene and gamete flow and mendelian sampling covariance matrices
### $Id: TDT.R 1193 2007-04-06 11:35:47Z ggorjan $
### Time-stamp: <2007-09-07 00:49:04 ggorjan>
###------------------------------------------------------------------------
### {{{ Gene flow matrix - T
###------------------------------------------------------------------------
geneFlowT <- function(x, sort=TRUE, names=TRUE, ...)
{
## --- Setup ---
ascendant <- getAscendantName(x)
if(length(ascendant) > 2)
stop("no method for pedigree with more than two ascendants")
if(sort) idOrig <- as.character(getId(x)) # for sort-back
## Pedigree must be extended and sorted
x <- checkAttributes(x, extended=TRUE, sorted=TRUE)
n <- nrow(x)
ret <- matrix(0, n, n) # n*n matrix
diag(ret) <- 1 # diagonal = 1
rownames(ret) <- colnames(ret) <- getId(x)
asc1 <- as.character(getFather(x))
asc2 <- as.character(getMother(x))
testAsc1 <- !isUnknown(asc1)
testAsc2 <- !isUnknown(asc2)
## individuals with at least one ascendant known
set <- which(!(!testAsc1 & !testAsc2))
## --- Core ---
for(i in set) { # loop over set
j <- 1:(i - 1) # ret is a lower triangular matrix
if(testAsc1[i]) tmp <- 0.5 * ret[asc1[i], j]
if(testAsc2[i]) tmp <- tmp + 0.5 * ret[asc2[i], j]
ret[i, j] <- tmp
}
## --- End ---
if(sort) ret <- ret[idOrig, idOrig]
if(!names) attr(ret, which="dimnames") <- NULL
ret
}
### }}}
### {{{ Inverse of gene flow matrix - Tinv
###------------------------------------------------------------------------
geneFlowTinv <- function(x, sort=TRUE, names=TRUE, ...)
{
ret <- - gameteFlowM(x, sort=sort, names=names, ...)
diag(ret) <- 1
ret
}
### }}}
### {{{ Gamete flow matrix - M
###------------------------------------------------------------------------
gameteFlowM <- function(x, sort=TRUE, names=TRUE, ...)
{
## --- Setup ---
ascendant <- getAscendantName(x)
if(length(ascendant) > 2)
stop("no method for pedigree with more than two ascendants")
if(sort) idOrig <- as.character(getId(x)) # for sort-back
## Pedigree must be extended and sorted FIXME?
x <- checkAttributes(x, extended=TRUE, sorted=TRUE)
n <- nrow(x)
ret <- matrix(0, n, n) # n*n matrix
rownames(ret) <- colnames(ret) <- getId(x)
asc1 <- as.character(getFather(x))
asc2 <- as.character(getMother(x))
testAsc1 <- !isUnknown(asc1)
testAsc2 <- !isUnknown(asc2)
## individuals with at least one ascendant known
set <- which(!(!testAsc1 & !testAsc2))
## --- Core ---
for(i in set) { # loop over set
if(testAsc1[i]) ret[i, asc1[i]] <- 0.5
if(testAsc2[i]) ret[i, asc2[i]] <- 0.5
}
## --- End ---
if(sort) ret <- ret[idOrig, idOrig]
if(!names) attr(ret, which="dimnames") <- NULL
ret
}
### }}}
### {{{ Mendelian sampling covariance matrix - D
###------------------------------------------------------------------------
mendelianSamplingD <- function(x, matrix=TRUE, names=TRUE, ...)
{
## --- Setup ---
ascendant <- getAscendantName(x)
if(length(ascendant) > 2)
stop("no method for pedigree with more than two ascendants")
n <- nrow(x)
ret <- vector(mode="numeric", length=n) # n vector ~ diagonal matrix
ret[] <- 1 # has maximally 1 (unknown parents)
sub <- as.character(getId(x))
asc1 <- as.character(getFather(x))
asc2 <- as.character(getMother(x))
testAsc1 <- !isUnknown(asc1)
testAsc2 <- !isUnknown(asc2)
## --- Core ---
inbF <- inbreeding(x=x)
## Known ascendant1
ret[testAsc1] <- ret[testAsc1] - 0.25 * (1 + inbF[asc1[testAsc1]])
## Known ascendant2
ret[testAsc2] <- ret[testAsc2] - 0.25 * (1 + inbF[asc2[testAsc2]])
## --- End ---
if(matrix) {
tmp <- matrix(0, nrow=n, ncol=n)
diag(tmp) <- ret
ret <- tmp
}
if(names & matrix) rownames(ret) <- colnames(ret) <- sub
if(names & !matrix) names(ret) <- sub
ret
}
### }}}
### {{{ Dear Emacs
## Local variables:
## folded-file: t
## End:
### }}}
###------------------------------------------------------------------------
### TDT.R ends here
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