droponemarker: Drop one marker at a time and determine effect on genetic map
In byandell/qtl: Tools for analyzing QTL experiments

Description Usage Arguments Value Author(s) See Also Examples

Drop one marker at a time from a genetic map and calculate the change in log likelihood and in the chromosome length, in order to identify problematic markers.

droponemarker(cross, chr, error.prob=0.0001,
                map.function=c("haldane","kosambi","c-f","morgan"),
                m=0, p=0, maxit=4000, tol=1e-6, sex.sp=TRUE,
                verbose=TRUE)

`cross`	An object of class `cross`. See `read.cross` for details.
`chr`	A vector specifying which chromosomes to test for the position of the marker. This should be a vector of character strings referring to chromosomes by name; numeric values are converted to strings. Refer to chromosomes with a preceding `-` to have all chromosomes but those considered. A logical (TRUE/FALSE) vector may also be used.
`error.prob`	Assumed genotyping error rate used in the calculation of the penetrance Pr(observed genotype \| true genotype).
`map.function`	Indicates whether to use the Haldane, Kosambi, Carter-Falconer, or Morgan map function when converting genetic distances into recombination fractions. (Ignored if m > 0.)
`m`	Interference parameter for the chi-square model for interference; a non-negative integer, with m=0 corresponding to no interference. This may be used only for a backcross or intercross.
`p`	Proportion of chiasmata from the NI mechanism, in the Stahl model; p=0 gives a pure chi-square model. This may be used only for a backcross or intercross.
`maxit`	Maximum number of EM iterations to perform.
`tol`	Tolerance for determining convergence.
`sex.sp`	Indicates whether to estimate sex-specific maps; this is used only for the 4-way cross.
`verbose`	If TRUE, print information on progress; if > 1, print even more information.

A data frame (actually, an object of class "scanone", so that one may use plot.scanone, summary.scanone, etc.) with each row being a marker. The first two columns are the chromosome ID and position. The third column is a LOD score comparing the hypothesis that the marker is not linked to the hypothesis that it belongs at that position.

In the case of a 4-way cross, with sex.sp=TRUE, there are two additional columns with the change in the estimated female and male genetic lengths of the respective chromosome, upon deleting that marker. With sex.sp=FALSE, or for other types of crosses, there is one additional column, with the change in estimated genetic length of the respective chromosome, when the marker is omitted.

A well behaved marker will have a negative LOD score and a small change in estimated genetic length. A poorly behaved marker will have a large positive LOD score and a large change in estimated genetic length. But note that dropping the first or last marker on a chromosome could result in a large change in estimated length, even if they are not badly behaved; for these markers one should focus on the LOD scores, with a large positive LOD score being bad.

Karl W Broman, kbroman@biostat.wisc.edu

tryallpositions, est.map, ripple, est.rf, switch.order, movemarker, drop.markers