gcp                   package:gap                   R Documentation

_P_e_r_m_u_t_a_t_i_o_n _t_e_s_t_s _u_s_i_n_g _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/PERMUTE program
     which generates EHPLUS-type statistics including z-tests for
     individual haplotypes

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

     gcp(y, cc, g, handle.miss=1, miss.val=0, n.sim=0, locus.label=NULL, quietly=FALSE)

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

       y: A column of 0/1 indicating cases and controls

      cc: analysis indicator, 0 = marker-marker, 1 = case-control

       g: the multilocus genotype data

handle.miss: a flag with value 1 indicating missing data are allowed

miss.val: missing value

   n.sim: the number of permutations

locus.label: label of each locus

 quietly: a flag if TRUE will suppress the screen output

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

     The returned value is a list containing (p.sim and ph when n.sim >
     0):

   x2obs: the observed chi-squared statistic

    pobs: the associated p value

    zobs: the observed z value for individual haplotypes

   p.sim: simulated p value for the global chi-squared statistic

      ph: simulated p values for individual haplotypes

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

     Zhao JH, Curtis D, Sham PC (2000). Model-free analysis and
     permutation  tests for allelic associations. Human Heredity 50(2):
     133-139

     Zhao JH (2004). 2LD, GENECOUNTING and HAP: Computer programs for
     linkage  disequilibrium analysis. Bioinformatics 20: 1325-1326

     Zhao JH, Qian WD Association analysis of unrelated individuals
     using polymorphic genetic markers - methods, implementation and
     application, Royal Statistical Society 2003, Hassallt-Diepenbeek,
     Belgium.

_N_o_t_e:

     Built on gcp.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(fsnps)
     y<-fsnps$y
     cc<-1
     g<-fsnps[,3:10]

     gcp(y,cc,g,miss.val="Z",n.sim=5)
     hap.score(y,g,method="hap",miss.val="Z")
     ## End(Not run)

