addqtl                  package:qtl                  R Documentation

_S_c_a_n _f_o_r _a_n _a_d_d_i_t_i_o_n_a_l _Q_T_L _i_n _a _m_u_l_t_i_p_l_e-_Q_T_L _m_o_d_e_l

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

     Scan for an additional QTL in the context of a multiple QTL model.

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

     addqtl(cross, chr, pheno.col=1, qtl, covar=NULL, formula,
            method=c("imp","hk"), incl.markers=TRUE, verbose=FALSE)

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

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

     chr: Optional vector indicating the chromosomes to be scanned. If
          missing, all chromosomes are scanned.

pheno.col: Column number in the phenotype matrix to be used as the
          phenotype.  One may also give a character string matching a
          phenotype name.

     qtl: An object of class 'qtl', as output from 'makeqtl'.

   covar: A data.frame of covariates.  These must be strictly numeric.

 formula: An object of class 'formula' indicating the model to be
          fitted.  QTLs are referred to as 'Q1', 'Q2', etc.  Covariates
          are referred to by their names in the data frame 'covar'.  If
          the new QTL is not included in the formula, its main effect
          is added.

  method: Indicates whether to use multiple imputation or Haley-Knott
          regression.

incl.markers: If FALSE, do calculations only at points on an evenly
          spaced grid.  If 'calc.genoprob' or 'sim.geno' were run with
          'stepwidth="variable"', we force 'incl.markers=TRUE'.

 verbose: If TRUE, display information about the progress of
          calculations.  If 'verbose' is an integer > 1, further
          messages from 'scanqtl' are also displayed.

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

     The formula is used to specified the model to be fit. In the
     formula, use 'Q1', 'Q2', etc., or 'q1', 'q2', etc., to represent
     the QTLs, and the column names in the covariate data frame to
     represent the covariates.

     We enforce a hierarchical structure on the model formula: if a QTL
     or covariate is in involved in an interaction, its main effect
     must also be included.   

     If one wishes to scan for QTL that interact with another QTL,
     include it in the formula (with an index of one more than the
     number of QTL in the input 'qtl' object).

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

     An object of class 'scanone', as produced by the 'scanone'
     function.  LOD scores are relative to the base model (with any
     terms that include the new QTL omitted).

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

     Karl W Broman, kbroman@biostat.wisc.edu

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

     Haley, C. S. and Knott, S. A. (1992) A simple regression method
     for mapping quantitative trait loci in line crosses using flanking
     markers. _Heredity_ *69*, 315-324.

     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:

     'scanone', 'fitqtl', 'scanqtl', 'refineqtl', 'makeqtl',
     'addtoqtl', 'addpair', 'addint'

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

     data(fake.f2)

     # take out several QTLs and make QTL object
     qc <- c(1, 8, 13)
     qp <- c(26, 56, 28)

     fake.f2 <- subset(fake.f2, chr=c(1,2,3,8,13))


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

     # scan for an additional QTL
     out1 <- addqtl(fake.f2, qtl=qtl, formula=y~Q1+Q2+Q3)
     max(out1)

     # scan for an additional QTL that interacts with the locus on chr 1
     out2 <- addqtl(fake.f2, qtl=qtl, formula=y~Q1*Q4+Q2+Q3)
     max(out2)

     # plot interaction LOD scores
     plot(out2-out1)

