Description Usage Arguments Details Value Examples
qtlStats
Pushes a QTL model through fitqtl and calculates confidence intervals.
1 2 |
cross |
The qtl cross object with marker names that need to be changed. |
mod |
A QTL model, generated by either makeqtl (etc.) or stepwiseqtl. |
pheno.col |
Character or numeric vector of length 1, indicating the phenotype to be tested |
form |
If a generic (not stepwiseqtl) qtl model is supplied and does not contain a formula, this is required. The formula must match the QTL in the fitted QTL (mod) object. |
covar |
the covariate specified in the model / formula. See fitqtl. |
calcConfint |
Should confidence intervals be calculated? If so, see ... Also ensure that lodprofiles are included in the model. |
estEffects |
Should allelic effects be calculated? |
model |
Should a normal or binary model be fit? |
... |
additional arguments passed on to calcCis. |
A simple method to produce stats from a fitted model. Calls several R/qtl functions depending on the user specifications. These include fitqtl, summary.fitqtl, bayesint, dropint, and qtlTools::calcCis. The method of QTL inference is extracted from the QTL model.
A dataframe of statistics.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | library(qtlTools)
data(fake.bc)
cross<-fake.bc
cross <- calc.genoprob(cross, step=2.5)
mod <- makeqtl(cross, chr = c(2,5), pos = c(40,25), what = "prob")
nform <- "y ~ Q1 + Q2 + Q1*sex + sex"
sex <- data.frame(sex = cross$phe$sex)
mod <- refineqtl(cross, mod, pheno.col = "pheno1", qtl = mod,
formula = nform, covar = sex, method="hk")
qtlStats(cross, pheno.col = "pheno1",form = nform, mod = mod, covar=sex)
data(fake.f2)
cross<-fake.f2
cross <- calc.genoprob(cross, step=2.5)
mod <- makeqtl(cross, chr = c(1,13), pos = c(27.5,27.5), what = "prob")
nform <- "y ~ Q1 + Q2 + Q1*sex + sex"
sex <- data.frame(sex = cross$phe$sex)
mod <- refineqtl(cross, mod, pheno.col = 1, qtl = mod,
formula = nform, covar = sex, method="hk")
qtlStats(cross, pheno.col = 1,form = nform, mod = mod, covar=sex)
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