configs                 package:bqtl                 R Documentation

_L_o_o_k_u_p _l_o_c_i _o_r _e_f_f_e_c_t_s _f_o_r _g_e_n_e_t_i_c _m_o_d_e_l _f_o_r_m_u_l_a_s

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

     Convert numeric indexes to names of regressors for a genetic
     model. One or many genetic models can be specified through the use
     of this function.  It is used on the right hand side of a formula
     in the 'bqtl' function.

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

     configs(x,...,scope=<<see below>>, method = NULL)

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

       x: Typically an integer, an integer vector, an array, or a list
          with a 'configs' component such as returned by 'swapbc1 '.
          However, it can also be a character string, vector, et
          cetera, in which case the elements must belong to
          'names(scope)' 

     ...: Optional arguments to be used when 'is.atomic(x)' is TRUE. 

   scope: (Optional and) 

          Usually not supplied by the user.  Rather 'bqtl' fills this
          in automatically.  A vector of regressor names, like the
          'reg.names' component returned by 'make.analysis.obj'.  When
          'mode(x)' is '"character"', then 'names(scope)' *must* be
          non-'NULL' 

  method: (Optional and) Usually not supplied by the user. A method
          like "F2". Typically, this is determined by internal code. 

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

     'configs' is used in the model formula notation of 'bqtl',
     possibly more than once, and possibly with regressors named in the
     usual manner.  'configs' is intended to speed up the specification
     and examination of genetic models by allowing many models to be
     specified in a shorthand notation in a single model formula.  The
     names of genetic loci can consist of marker names, names that
     encode chromosome number and location, or other shorthand
     notations.  The names of terms in genetic models will typically
     include the names of the locus and may prepend "add." or "dom." or
     similar abbreviations for the 'additive' and 'dominance' terms
     associated with the locus. 

     When used as in 'bqtl( y ~ configs(34), my.analysis.obj )', it
     will look up the term 'my.analysis.obj$reg.names[34]'.  When this
     is passed back to 'bqtl', it get pasted into the formula and is
     subsequently processed to yield the fit for a one gene model.

     When used as in 'bqtl( y ~ configs(34,75,172), my.analysis.obj)'
     it looks up each term and returns a result to 'bqtl' that results
     in fitting a 3 gene model (without interaction terms). 

     When 'x' is a vector, array, or list, the processing typically
     returns pieces of many model formulas.  'bqtl(y ~ configs(26:75),
     ...)' results in a list of 50 different one gene model fits from
     'bqtl' for the terms corresponding to the 26th through the 75th
     variables.  ' bqtl(y ~
     configs(cbind(c(15,45,192),c(16,46,193))),...)' returns two four
     gene models.  And more generally, whenever 'is.array(x)' is TRUE,
     the columns (or slices) specify ' dim(x)[1]/length(x)' different
     models.  When 'x$configs' is an array, this also happens.  This
     turns out to be useful when the result of running 'swapbc1' or
     'swapf2' is treated as an importance sample.  In such a case,
     'bqtl(y ~ configs(my.swap),my.analysis.obj)' will return a list in
     which element 'i' is the ith sample drawn when 'my.swap <-
     swapbc1(...)' was run.

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

     A character vector whose element(s) can be parsed as the right
     hand side of a model formula.

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

     Charles C. Berry cberry@ucsd.edu

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

     'bqtl' and the examples there for a sense of how to use 'configs',
      'make.analysis.obj' for the setup that encodes the marker map and
     the marker information, 'swapbc1' and  'swapf2' for generating
     samples to be screened by 'bqtl'.

