dlcross.cross(genobj, pheobj, idname, step, fixpos, estmap)
dlcross.dlmap(genobj, pheobj, mapobj, idname, genfile, mapfile, phefile, type, step, fixpos, estmap, ...)
dlcross.other(genobj, pheobj, mapobj, idname, genfile, mapfile, phefile)
dldetect(input, algorithm, filestem, ...)
dllocalize(input, algorithm, QTLperChr, ...)
dlmapdet(input, algorithm, s.chr, chrSet, prevLoc = NULL, ...)
dlmaploc(input, algorithm, s.chr, chrSet, prevLoc = NULL, ...)
dltest(input, algorithm, chrSet, prevLoc = NULL, ...)
calcpos(cross, step, fixpos)
calc.genoprob2(cross, pos, error.prob=1e-04, map.function=c("haldane", "kosambi", "c-f", "morgan"))
waldtest.asreml(object, cc)
cintern(cc, tau, vrb, sigma2)algorithm allows for versions using
either lme or asreml to fit mixed models. The merge function is used to combine the genotype and environmental data,
and also imputes missing values in the genotype data according to the Viterbi
algorithm. See fill.geno for more details. Note that
individuals with no phenotypic response data are omitted in the merged
dataset. Individuals with phenotypic but no genotypic data are retained, but
the genotypes are not imputed.
calc.genoprob2 is a modification of a function from the R/qtl package to allow for calculation of genotype probabilities at more general positions than a fixed step size.
Broman et al. (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19:889-890
B. Emma Huang, Rohan Shah, Andrew W. George (2012). dlmap: An R Package for Mixed Model QTL and Association Analysis. Journal of Statistical Software 50(6): 1-22. URL http://www.jstatsoft.org/v50/i06/.