ripple                  package:qtl                  R Documentation

_C_o_m_p_a_r_e _m_a_r_k_e_r _o_r_d_e_r_s

_D_e_s_c_r_i_p_t_i_o_n:

     Investigate different marker orders for a given chromosome,
     comparing all possible permutations of a sliding window of
     markers.

_U_s_a_g_e:

     ripple(cross, chr, window=4, method=c("countxo","likelihood"),
            error.prob=0, map.function=c("haldane","kosambi","c-f","morgan"),
            maxit=4000, tol=1e-4, sex.sp=TRUE)

_A_r_g_u_m_e_n_t_s:

   cross: An object of class 'cross'. See 'read.cross' for details.

     chr: The chromosome to investigate.  Only one chromosome is
          allowed.

  window: Number of markers to include in the sliding window of
          permuted markers.  Larger numbers result in the comparison of
          a greater number of marker orders, but will require a
          considerable increase in computation time.

  method: Indicates whether to compare orders by counting the number of
          obligate crossovers, or by a likelihood analysis.

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.

   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.

_D_e_t_a_i_l_s:

     For 'method="likelihood"', calculations are done by first
     constructing a matrix of marker orders and then making repeated
     calls to the R function 'est.map'.  Of course, it would be faster
     to do everything within C, but this was a lot easier to code.

     For 'method="countxt"', calculations are done within C.

_V_a_l_u_e:

     A matrix, given class '"ripple"'; the first set of columns are
     marker indices describing the order.  In the case of
     'method="countxo"', the last column is the number of obligate
     crossovers for each particular order.  In the case of
     'method="likelihood"', the last two columns are LOD scores (log
     base 10 likelihood ratios) comparing each order to the initial
     order and the estimated chromosome length for the given order. 
     Positive LOD scores indicate that the alternate order has more
     support than the original.

_A_u_t_h_o_r(_s):

     Karl W Broman, kbroman@jhsph.edu

_S_e_e _A_l_s_o:

     'summary.ripple', 'switch.order', 'est.map', 'est.rf'

_E_x_a_m_p_l_e_s:

     data(badorder)
     rip7c <- ripple(badorder, chr=1, window=3)
     summary(rip7c)

     ## Not run: 
     rip2l <- ripple(badorder, chr=1, window=2, method="likelihood")
     summary(rip2l)
     ## End(Not run)

     badorder <- switch.order(badorder, 1, rip7c[2,])

