initialDesign            package:designGG            R Documentation

_I_n_i_t_i_a_l_i_z_e _a_n _e_x_p_e_r_i_m_e_n_t _d_e_s_i_g_n _m_a_t_r_i_x

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

     Allocate RILs (or strains) into different conditional and pair
     RILs (or strains) into slides.

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

       initialDesign( genotype, nRILs, nSlides, nConditions, nTuple, 
                      bTwoColorArray )

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

genotype: genotype data: a nMarker-by-nRILs matrix with two allels
          being 0 and 1 (or A and B) or three allels being 0, 0.5 and 1
          (or, A, H, and B), where 0.5 (or H) represents heterozygous
          allele.  

   nRILs: total number of RILs ((or strains) available for the
          experiment.  

 nSlides: total number of slides available for the experiment.  

nConditions: number of all possible combination of all environmental
          factors.   

  nTuple: average number of RILs (or strains) to be assigned onto each
          condition 
           'nTuple' should be a real number which is larger than 1.
           if 'nTuple' < 1, the algorithm will stop and shw the message
          below, 
           'warning: "The number of slides is too small to perform the
          experiment."' 

bTwoColorArray: binary variable indicating experiment type: 
           'bTwoColorArray <- T' #for dual channel experiment 
           'bTwoColorArray <- F' #for single channel experiment  

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

     For two-color array experiments, randomly choose a RIL (or strain)
     and pair it with the  genetically most different RIL (or strain)
     on one array. 
      For one-color array experiments, array.allocation is 'NULL' as
     there is no  need to pair samples.

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

     a list with 2 matrices:  
      'condition.allocation': allocate RILs (or strains) into different
     conditional (nCondition $\times$ nRILs)      
      'array.allocation': pair RILs (or strains) into sldies (nSlides
     $\times$ nRILs)

_N_o_t_e:

     This function calls 'conditionAllocation' function to allocate
     selected RILs  (or strains) into different conditions.

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

     Yang Li <yang.li@rug.nl>, Gonzalo Vera
     <gonzalo.vera.rodriguez@gmail.com> 
      Rainer Breitling <r.breitling@rug.nl>, Ritsert Jansen
     <r.c.jansen@rug.nl>

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

     Y. Li, R. Breitling and R.C. Jansen. Generalizing genetical
     genomics: the added value from environmental perturbation, Trends
     Genet (2008) 24:518-524. 
      Y. Li, M. Swertz, G. Vera, J. Fu, R. Breitling, and R.C. Jansen.
     designGG: An R-package and Web tool for the optimal design of
     genetical genomics experiments. (submitted) 
      http://gbic.biol.rug.nl/designGG

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

     'designGG'

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

     genotype <- read.table("genotype.txt")
     nEnvFactors <- 2  
     nLevels <- c( 2, 2 )
     levels <- list ( c(16, 24), c(5, 10) )
     nSlides <- 100
     nTuple <- 25  
     bTwoColorArray <- TRUE 
     initialDesign( genotype, nRILs, nSlides, nConditions, nTuple, bTwoColorArray )          

