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
. See
read.cross
for details.
"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.
tryallpositions
, est.map
, ripple
,
est.rf
, switch.order
,
movemarker
, drop.markers
data(fake.bc)
droponemarker(fake.bc, 7, error.prob=0, verbose=FALSE)
Run the code above in your browser using DataLab