mporder(object, chr, type = c("2", "m"), mapfx = c("haldane", "kosambi"), rm.rf = TRUE, window = 3, repeats = 1, criterion = c("Path_length", "AR_events", "AR_deviations", "Gradient_raw", "Inertia", "Least_squares", "minXO", "lkhdsum"), missfx = 2, ...)mpcrossfilladd3pt
later. Multiple methods are used to investigate optimal
two-point orderings. These are taken from the package
seriation and include simulated annealing,
hierarchical clustering, and traveling salesman solver.
The orders are compared on the basis of the argument
criterion. Thus the total path length, or sum of
adjacent recombination fractions can be minimized; or the
number of Anti-Robinson events/deviations; or the number
of crossovers; or the sum of the adjacent two-point LOD
scores.
Multi-point ordering The multi-point ordering
assumes that there is a pre-existing map, and then
repeatedly applies the ripple function in R/qtl to
investigate local permutations of the order. These
orderings are constrained by the arguments window
and repeats, which determine how large the
perturbations are and how many are considered. Large
values of window are very time consuming;
recommended values are 5 or less, due to the number of
permutations which must be considered. Large values of
repeats will eventually converge to an ordering in
which all local rearrangements of size window have
been optimized with respect to the number of crossovers.
mpestrf,
mpgroup,
add3pt,
seriate,
ripple