calc.penalties | R Documentation |
Derive penalties for the penalized LOD scores (used by
stepwiseqtl
) on the basis of permutation results
from a two-dimensional, two-QTL scan (obtained by scantwo
).
calc.penalties(perms, alpha=0.05, lodcolumn)
perms |
Permutation results from |
alpha |
Significance level. |
lodcolumn |
If the scantwo permutation results contain LOD scores for multiple phenotypes, this argument indicates which to use in the summary. This may be a vector. If missing, penalties for all phenotypes are calculated. |
Thresholds derived from scantwo
permutations (that
is, for a two-dimensional, two-QTL genome scan) are used to calculate
penalties on main effects and interactions.
The main effect penalty is the 1-alpha
quantile of the null
distribution of the genome-wide maximum LOD score from a single-QTL
genome scan (as with scanone
).
The "heavy" interaction penalty is the 1-alpha
quantile of
the null distribution of the maximum interaction LOD score (that is,
the \log_{10}
likelihood ratio comparing the best model
with two interacting QTL to the best model with two additive QTL) from
a two-dimensional, two-QTL genome scan (as with
scantwo
).
The "light" interaction penality is the difference between the
"fv1"
threshold from the scantwo
permutations (that is, the 1-alpha
quantile of the LOD score
comparing the best model with two interacting QTL to the best
single-QTL model) and the main effect penalty.
If the permutations results were obtained with perm.Xsp=TRUE
,
to give X-chr-specific results, six penalties are calculated: main
effect for autosomes, main effect for X chr, heavy penalty on A:A
interactions, light penalty on A:A interactions, penalty on A:X
interactions, and penalty on X:X interactions.
Vector of three values indicating the penalty on main effects and heavy and light penalties on interactions, or a matrix of such results, with each row corresponding to a different phenotype.
If the input permutations are X-chromosome-specific, the result has six values: main effect for autosomes, main effect for X chr, heavy penalty on A:A interactions, light penalty on A:A interactions, penalty on A:X interactions, and penalty on X:X interactions.
Karl W Broman, broman@wisc.edu
Manichaikul, A., Moon, J. Y., Sen, Ś, Yandell, B. S. and Broman, K. W. (2009) A model selection approach for the identification of quantitative trait loci in experimental crosses, allowing epistasis. Genetics, 181, 1077–1086.
scantwo
, stepwiseqtl
data(fake.f2)
fake.f2 <- calc.genoprob(fake.f2, step=5)
out.2dim <- scantwo(fake.f2, method="hk")
# permutations
## Not run: permo.2dim <- scantwo(fake.f2, method="hk", n.perm=1000)
summary(permo.2dim, alpha=0.05)
# penalties
calc.penalties(permo.2dim)
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