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######################################################################
#
# vbscan.R
#
# copyright (c) 2001-7, Karl W Broman
# last modified Jul, 2007
# first written May, 2001
# Licensed under the GNU General Public License version 2 (June, 1991)
#
# Part of the R/qtl package
# Contains: vbscan
#
######################################################################
######################################################################
#
# vbscan: scan genome for a quantitative phenotype for which some
# individuals' phenotype is undefined (for example, the size of a
# lesion, where some individuals have no lesion).
#
######################################################################
vbscan <-
function(cross, pheno.col=1, upper=FALSE, method="em", maxit=4000,
tol=1e-4)
{
method <- match.arg(method)
type <- class(cross)[1]
# check arguments are okay
if(length(pheno.col) > 1) pheno.col <- pheno.col[1]
if(pheno.col > nphe(cross))
stop("Specified phenotype column exceeds the number of phenotypes")
y <- cross$pheno[,pheno.col]
# modify phenotypes
if(upper) {
if(!any(y == Inf)) y[y==max(y)] <- Inf
}
else {
if(!any(y == -Inf)) y[y==min(y)] <- -Inf
}
survived <- rep(0,length(y))
survived[y == -Inf | y == Inf] <- 1
# The following line is included since .C() doesn't accept Infs
y[y == -Inf | y == Inf] <- 99999
n.chr <- nchr(cross)
results <- NULL
# to store the degrees of freedom
dfApm <- dfAp <- dfAm <- -1
dfXpm <- dfXp <- dfXm <- -1
for(i in 1:n.chr) {
# make sure inferred genotypes or genotype probabilities are available
if(!("prob" %in% names(cross$geno[[i]]))) {
cat(" -Calculating genotype probabilities\n")
cross <- calc.genoprob(cross)
}
genoprob <- cross$geno[[i]]$prob
n.pos <- dim(genoprob)[2]
n.ind <- length(y)
chrtype <- class(cross$geno[[i]])
if(chrtype=="X") sexpgm <- getsex(cross)
else sexpgm <- NULL
gen.names <- getgenonames(type,chrtype,"full", sexpgm, attributes(cross))
n.gen <- length(gen.names)
# revise X chromosome genotypes
if(chrtype=="X" && (type=="f2" || type=="bc"))
genoprob <- reviseXdata(type, "full", sexpgm, prob=genoprob,
cross.attr=attributes(cross))
z <- .C("R_vbscan",
as.integer(n.pos),
as.integer(n.ind),
as.integer(n.gen),
as.double(genoprob),
as.double(y),
as.integer(survived),
lod=as.double(rep(0, n.pos*3)),
as.integer(maxit),
as.double(tol),
PACKAGE="qtl")
if("map" %in% names(attributes(cross$geno[[i]]$prob)))
map <- attr(cross$geno[[i]]$prob,"map")
else {
stp <- attr(cross$geno[[i]]$prob, "step")
oe <- attr(cross$geno[[i]]$prob, "off.end")
if("stepwidth" %in% names(attributes(cross$geno[[i]]$prob)))
stpw <- attr(cross$geno[[i]]$prob, "stepwidth")
else stpw <- "fixed"
map <- create.map(cross$geno[[i]]$map,stp,oe,stpw)
}
if(is.matrix(map)) map <- map[1,]
res <- data.frame(chr=rep(names(cross$geno)[i],length(map)),
pos = as.numeric(map),
matrix(z$lod,nrow=n.pos,byrow=TRUE))
colnames(res)[-(1:2)] <- c("lod.p.mu","lod.p","lod.mu")
w <- names(map)
o <- grep("^loc-*[0-9]+",w)
if(length(o) > 0) # inter-marker locations cited as "c*.loc*"
w[o] <- paste("c",names(cross$geno)[i],".",w[o],sep="")
rownames(res) <- w
z <- res
if(chrtype=="A" && dfApm < 0) {
dfApm <- (n.gen-1)*2
dfAp <- (n.gen-1)
dfAm <- (n.gen-1)
}
# get null log10 likelihood for the X chromosome
if(chrtype=="X") {
# determine which covariates belong in null hypothesis
temp <- scanoneXnull(type, sexpgm)
adjustX <- temp$adjustX
parX0 <- temp$parX0
sexpgmcovar <- temp$sexpgmcovar
sexpgmcovar.alt <- temp$sexpgmcovar.alt
if(dfXpm < 0) {
if(adjustX) nc <- ncol(sexpgmcovar)
else nc <- 1
dfXp <- dfXm <- n.gen - nc
dfXpm <- 2*dfXp
}
if(adjustX) { # get LOD-score adjustment
n.gen <- ncol(sexpgmcovar)+1
genoprob <- matrix(0,nrow=n.ind,ncol=n.gen)
for(i in 1:n.gen)
genoprob[sexpgmcovar.alt==i,i] <- 1
nullz <- .C("R_vbscan",
as.integer(1),
as.integer(n.ind),
as.integer(n.gen),
as.double(genoprob),
as.double(y),
as.integer(survived),
lod=as.double(rep(0,(4+2*n.gen))),
as.integer(maxit),
as.double(tol),
PACKAGE="qtl")
# adjust LOD curve
for(i in 1:3) z[,i+2] <- z[,i+2] - nullz$lod[i]
}
}
results <- rbind(results, z)
}
class(results) <- c("scanone","data.frame")
attr(results,"method") <- method
attr(results,"type") <- class(cross)[1]
attr(results,"model") <- "twopart"
df <- NULL
if(dfApm > 0)
df <- rbind(df, "A"=c("p.mu"=dfApm, "p"=dfAp, "mu"=dfAm))
if(dfXpm > 0)
df <- rbind(df, "X"=c("p.mu"=dfXpm, "p"=dfXp, "mu"=dfXm))
attr(results, "df") <- df
results
}
# end of vbscan.R
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