pgc                   package:gap                   R Documentation

_P_r_e_p_a_r_i_n_g _w_e_i_g_h_t _f_o_r _G_E_N_E_C_O_U_N_T_I_N_G

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

     This function is a R port of the GENECOUNTING/PREPARE program
     which takes an array of genotyep data and collapses individuals
     with the same multilocus genotype

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

     pgc(data,handle.miss=1,is.genotype=0,with.id=0)

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

    data: the multilocus genotype data for a set of individuals

handle.miss: a flag to indicate if missing data is kept, 0 = no, 1 =
          yes

is.genotype: a flag to indicate if the data is already in the form of
          genotype identifiers

 with.id: a flag to indicate if the unique multilocus genotype
          identifier is generated

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

     The returned value is a list containing:

    gret: the collapsed genotype data

      wt: the frequency weight

  obscom: the observed number of combinations or genotypes

  idsave: optional, available only if with.id = 1

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

     Zhao JH, Sham PC (2003). Generic number system and haplotype
     analysis. Comp Prog Meth Biomed 70:1-9

_N_o_t_e:

     Built on pgc.c

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

     Jing hua Zhao

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

     'genecounting'

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

     ## Not run: 

     data(hla)
     x <- hla[,3:8]

     # do not handle missing data
     y<-pgc(x,handle.miss=0,with.id=1)
     hla.gc<-genecounting(y$cdata,y$wt,handle.miss=0)

     # handle missing but with multilocus genotype identifier
     pgc(x,handle.miss=1,with.id=1)

     # handle missing data with no identifier
     pgc(x,handle.miss=1,with.id=0)
     ## End(Not run)

