qb.data                package:qtlbim                R Documentation

_P_r_e_p_a_r_e_s _d_a_t_a _f_o_r _q_b._m_c_m_c

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

     This function selects trait(s) and covariates from a 'cross'
     object to build a model ('qb.model') for MCMC ('qb.mcmc').

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

     qb.data( cross, pheno.col = 1, trait = c("normal","binary","ordinal"), 
       fixcov = c(0), rancov = c(0), boxcox = FALSE, standardize = FALSE, ...) 

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

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

pheno.col: the column number for the phenotype used by 'model'. 
          Currently, only one phenotype can be analyzed at a time.

   trait: Type of the quatitative trait or dependent variable: 
          "normal" or "binary" or "ordinal".

  fixcov: list of fixed covariates. The column number(s) in
          'cross$pheno' which is(are) considered as fixed covariates.

  rancov: list of random covariates.The column number(s) in
          'cross$pheno' which is(are) considered as random covariates.

  boxcox: Indicates whether to use a Boxcox transformation for the 
          dependent variable or not: TRUE or FALSE. Note: trait has to
          be "normal" and all phenotypic values have to be positive for
          using this option.

standardize: Indicates whether to standardize the dependent variable or
          not:  TRUE or FALSE. Note: trait has to be "normal" to use
          this option.

     ...: Extra terms not used.

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

     This function picks the relevant part of the data from the 'cross'
     object and prepares data for 'qb.model' and 'qb.mcmc' It can also
     standardize or transform continuous data if specified.

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

  yvalue: vector of the values of the dependent variable.

ncategory: number of category type if it is non-normal data.

    envi: environment effect: TRUE or FALSE.

 nfixcov: number of fixed covariates.

 nrancov: number of random covariates.

 fixcoef: values of the fixed covariate(s) for all individuals.

 rancoef: values of the random covariate(s) for all individuals.

    nran: number of categories defining the random covariate.

   lamda: value of lamda, the transformation parameter for the 'boxcox'
          transformation.

_N_o_t_e:

     This function returns a list and hence should have a differenct
     name from that of the 'cross' object.

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

     Dr. Nengjun Yi, et al.,  nyi@ms.ssg.uab.edu

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

     <URL: http://www.qtlbim.org>

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

     'qb.genoprob',  'qb.model',   'qb.mcmc'

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

     qbData <- qb.data(cross, pheno.col = 3, rancov = 2, fixcov = 1)

