makeqtl                 package:qtl                 R Documentation

_M_a_k_e _a _q_t_l _o_b_j_e_c_t

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

     This function takes a cross object and specified chromosome
     numbers and positions and pulls out the genotype probabilities
     and/or imputed genotypes at the nearest pseudomarkers, for later
     use by the function 'fitqtl'.

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

     makeqtl(cross, chr, pos, qtl.name)

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

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

     chr: Vector indicating the chromosome for each QTL.

     pos: Vector (of same length as 'chr') indicating the positions on
          the chromosome to be taken. If there's no marker or
          pseudomarker at a position, genotypes for the nearest
          positions are taken.

qtl.name: The user-specified name for each QTL, used in the
          drop-one-term ANOVA table in 'fitqtl'. If unspecified, the
          names will be of the form '"Chr1@10"' for a QTL on Chromsome
          1 at 10 cM.

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

     This function will take out the genotype probabilities and imputed
     genotypes if they are present in the input 'cross' object. If both
     fields are missing in the input object, the function will report
     an error. Before running this function, the user must have first
     run either 'calc.geno' or 'sim.geno'.

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

     An object of class 'qtl' with the following elements: 

    geno: Imputed genotypes.

    prob: Genotype probabilities.

     chr: Input vector of chromosome numbers.

     pos: Input vector of chromosome positions.

   n.qtl: Number of QTLs.

   n.ind: Number of individuals.

   n.gen: A vector indicating the number of genotypes for each QTL.

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

     Hao Wu, hao@jax.org

_R_e_f_e_r_e_n_c_e_s:

     Sen, S. and Churchill, G. A. (2001) A statistical framework for
     quantitative trait mapping.  _Genetics_ *159*, 371-387.

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

     'fitqtl', 'calc.genoprob', 'sim.geno'

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

     data(fake.f2)

     # take out several QTLs and make QTL object
     qc <- c(1, 6, 13)
     qp <- c(25.8, 33.6, 18.63)
     fake.f2 <- subset(fake.f2, chr=qc)

     fake.f2 <- sim.geno(fake.f2, n.draws=8, step=2, err=0.001)
     qtl <- makeqtl(fake.f2, qc, qp)

