summary.scanone {qtl} | R Documentation |
Print the rows of the output from scanone
that
correspond to the maximum LOD for each chromosome, provided that they
exceed some specified thresholds.
summary.scanone(..., threshold=0)
... |
One or several objects output by the function
scanone . |
threshold |
LOD score thresholds. Only peaks with LOD score above this value will be returned. This could be a scalar, a vector or a matrix. See below section for details. |
This function is used to report locus deemed interesting for a one-QTL
genome scan. Users can provide one or more results from
scanone
and one or more thresholds corresponding to
different significance levels. For multiple scanone results case, a loci
will be reported if any of the LOD scores exceeds the minimum of the
corresponding threshold.
A column is significance code will be printed for each column of LOD score. It will use "stars" to visualize the significance level. That is, if the LOD score exceeds the lowest threshold, it will have one star (*). If it exceeds the second lowest threshold, it will have two stars (**) and so on.
The input threshold
could be a scalar, a vector or a matrix. The
way threshold
works is like the following:
scanone
result case.
scanone
result case.
Usually the threshold should be obtained from the permutation
test. Users can use quantile
to get a list of
threhold values for different significance levels.
An object of class summary.scanone
, to be printed by
print.summary.scanone
. This is a data.frame with one row per
chromosome, corresponding to the maximum LOD scores.
Karl W Broman, kbroman@jhsph.edu; Hao Wu, hao@jax.org
scanone
, plot.scanone
,
max.scanone
, quantile
data(fake.f2) fake.f2 <- calc.genoprob(fake.f2) # scanones on observed data scan1 <- scanone(fake.f2, pheno.col=1) # permutation tests ## Not run: out1 <- scanone(fake.f2, pheno.col=1, n.perm=100) ## End(Not run) ###### summary one result ####### # one sig level summary(scan1, threshold=quantile(out1, 0.95)) # multiple sig level summary(scan1, threshold=quantile(out1, c(0.63,0.95,0.99))) # scan the other phenotype scan2 <- scanone(fake.f2, pheno.col=2) ## Not run: out2 <- scanone(fake.f2, pheno.col=2, n.perm=100) ## End(Not run) ##### summary multiple results # one sig level summary(scan1,scan2, threshold=2) # multiple sig level, same threshold summary(scan1, scan2,threshold=matrix(quantile(out1,c(0.37,0.95,0.99)),ncol=1)) # one sig level, different threshold summary(scan1, scan2,threshold=c(3,0.8)) # multiple sig level, different threshold threshold <- matrix(c(quantile(out1,probs=c(0.37,0.95,0.99)),0.5,0.8,1.2), ncol=2) summary(scan1, scan2, threshold=threshold)