Usage
addqtl(cross, qtl, add.chr, add.pos, add.name, map)
adjust.rf.ri(r, type=c("self","sib"), chrtype=c("A","X"), expand=TRUE)
calc.pairprob(cross, step=0, off.end=0, error.prob=0.0001,
map.function=c("haldane","kosambi","c-f","morgan"))
checkcovar(cross, pheno.col, addcovar, intcovar)
checkrf(cross, threshold)
convert.cross(cross)
create.map(map, step, off.end)
discan(cross, pheno, method=c("em","mr"),
addcovar=NULL, intcovar=NULL, maxit=4000, tol=1e-4,
verbose=FALSE)
dropqtl(qtl, drop)
fixX4write(geno,sex,pgm,crosstype)
fixXgeno.bc(cross)
fixXgeno.f2(cross)
getsex(cross)
getgenonames(type=c("f2","bc","f2ss","riself","risib","4way"),
chrtype=c("A","X"), expandX=c("simple","standard","full"),
sexpgm)
imf.cf(r)
imf.h(r)
imf.k(r)
imf.m(r)
locatemarker(map, pos, chr, flag)
locate.xo(cross)
makeSSmap(cross)
mf.cf(d)
mf.h(d)
mf.k(d)
mf.m(d)
parseformula(formula, qtl.dimname, covar.dimname)
## S3 method for class 'summary.cross':
print(x, \dots)
## S3 method for class 'summary.fitqtl':
print(x, \dots)
## S3 method for class 'summary.map':
print(x, \dots)
## S3 method for class 'summary.ripple':
print(x, \dots)
## S3 method for class 'summary.scanone':
print(x, \dots)
## S3 method for class 'summary.scantwo':
print(x, \dots)
read.cro.qtlcart(file)
read.cross.csv(dir, file, na.strings=c("-","NA"),
genotypes=c("A","H","B","D","C"),
estimate.map=TRUE, rotate=FALSE, ...)
read.cross.csvs(dir, genfile, phefile, na.strings=c("-","NA"),
genotypes=c("A","H","B","D","C"),
estimate.map=TRUE, rotate=FALSE, ...)
read.cross.gary(dir, genfile, mnamesfile, chridfile, phefile,
pnamesfile, mapfile,estimate.map,na.strings)
read.cross.karl(dir, genfile, mapfile, phefile)
read.cross.mm(dir, rawfile, mapfile, estimate.map=TRUE)
read.cross.qtlcart(dir, crofile, mapfile)
read.cross.qtx(dir, file, estimate.map=TRUE)
read.map.qtlcart(file)
read.maps.mm(mapsfile)
replaceqtl(cross, qtl, replace, by.chr, by.pos, by.name, map)
revisecovar(sexpgm, covar)
reviseXdata(type=c("f2ss","f2","bc"), expandX=c("simple","standard","full"),
sexpgm, geno, prob, draws, pairprob)
ripple.perm1(n)
ripple.perm2(n)
ripple.perm.sub(x, mat)
scanone.perm(cross, pheno.col=1, model=c("normal","binary","2part","np"),
method=c("em","imp","hk","mr","mr-imp","mr-argmax"),
addcovar=NULL, intcovar=NULL, weights=NULL,
upper=FALSE, ties.random=FALSE, start=NULL, maxit=4000,
tol=1e-4, n.perm=1000, verbose=TRUE)
scanoneXnull(type, sexpgm)
scantwo.perm(cross, pheno.col=1,
method=c("em","imp","hk","mr","mr-imp","mr-argmax"),
model=c("normal","binary"),
addcovar=NULL, intcovar=NULL, weights=NULL,
incl.markers=FALSE, maxit=4000, tol=1e-4, verbose=FALSE,
n.perm=1000)
sim.cc(parents, n.ril=1, error.prob=0, missing.prob=0, m=0, step=0)
sim.cross.4way(map, model, n.ind, error.prob, missing.prob,
partial.missing.prob, keep.errorind, map.function)
sim.cross.bc(map, model, n.ind, error.prob, missing.prob,
keep.errorind, map.function)
sim.cross.f2(map, model, n.ind, error.prob, missing.prob,
partial.missing.prob, keep.errorind, map.function)
sim.ril(map, n.ril=1, n.str=c("2","4","8"), m=0, random.cross=TRUE)
## S3 method for class 'scantwo':
subset(x, chr, \dots)
vbscan(cross, pheno.col=1, upper=FALSE, method="em", maxit=4000,
tol=1e-4)
write.cross.csv(cross, filestem="data", digits=5)
write.cross.gary(cross, digits)
write.cross.mm(cross, filestem="data", digits=5)
write.cross.qtlcart(cross, filestem="data")