Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/stepwiseqtl_shape.R
Runs a stepwise multiple QTL model search using penalized negative $log_10$ of the p-value
1 2 3 4 |
cross |
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chr |
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pheno.col |
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qtl |
|
formula |
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max.qtl |
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covar |
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refine.locations |
Logical |
additive.only |
Logical. (Defauft FALSE).
(Not as in |
scan.pairs |
Logical. (Default FALSE) #keep it default. Not use so far |
penalties |
Genomewide threshold |
keeplodprofile |
Logical (Default TRUE) |
keeptrace |
Logical (Default FALSE) |
verbose |
Logical (Default FALSE) |
test |
Multivariate statistics (Default "Pillai". Others are : "Hotelling.Lawley", "Lik.ratio", "Goodall") |
The function built multiple QTL models using penalized negative $log_10$ of the p-value (as a multivariate analogue of the penalized LOD score of the R/qtl package). The search is limited so far to a model without interaction
The function returns a qtl object.
Nicolas Navarro
Broman and Sen 2009. A guide to QTL mapping with R/qtl
1 2 3 4 5 6 7 8 | data(fake.bc)
fake.bc <- calc.genoprob(fake.bc, step=2.5)
fake.bc <- update.cross(fake.bc, phen2keep = names(fake.bc$pheno)) #Just update the class of fake.bc
covar <- fake.bc$pheno[, c('sex','age')]
out1 <- scanoneShape(fake.bc, pheno.col = 1:2, addcovar = covar,
test = "Pillai")
Q <- max(out1)
outStep <- stepwiseqtlShape(fake.bc, pheno.col = 1:2, qtl = Q, max.qtl = 3, covar = covar, penalties=2.5, verbose = TRUE)
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