ccPred                 package:BGmix                 R Documentation

_R_e_a_d _p_r_e_d_i_c_t_i_v_e _q_u_a_n_t_i_t_i_e_s _o_u_t_p_u_t _f_r_o_m _B_G_m_i_x.

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

     Reads predictive p-values from files output from BGmix. Also
     (optionally) reads posterior predictive distributions of data.

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

     ccPred(filedir, q.partial = T, q.trace = F, quiet = T)

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

 filedir: character. The name of the output directory created by BGmix.

q.partial: logical. Read partial predictive p-values?

 q.trace: logical. Read posterior predictive distributions of data?

   quiet: logical. Parameter passed to 'scan'. (If false, 'scan' prints
          details of number of items read in.)

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

pval.ss.post: matrices no. genes x no. conditions. Posterior predictive
          p-values for sum of squares for each gene in each condition.

pval.ss.mix: matrices no. genes x no. conditions. Mixed predictive
          p-values for sum of squares for each gene in each condition.

pval.ss.part: matrices no. genes x no. conditions. Partial predictive
          p-values for sum of squares for each gene in each condition.

pval.ybar.post: matrices no. genes x no. mixture components. Posterior
          predictive p-values for ybar for each gene in each mixture
          component.

pval.ybar.mix2: matrices no. genes x no. mixture components. Mixed
          predictive p-values for ybar for each gene in each mixture
          component.

pval.ybar.part: matrices no. genes x no. mixture components. Partial
          predictive p-values for ybar for each gene in each mixture
          component.

ybar.pred1: Posterior predictive distribution of ybar.

ybar.pred3: Mixed predictive distribution of ybar.

ss.pred1: Posterior predictive distribution of sums of squares.

ss.pred2: Mixed predictive distribution of sums of squares.

_N_o_t_e:

     Additional output: pval.ybar.mix1 and pval.ybar.mix3 are
     alternative versions of mixed predictive p-values (currently not
     used). Also, ybar.pred2 and ybar.pred4 are the corresponding
     alternative mixed predictive distributions for ybar.

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

     Alex Lewin

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

     ## Note this is a very short MCMC run!
     ## For good analysis need proper burn-in period.
     data(ybar,ss)
     outdir <- BGmix(ybar, ss, c(8,8), nburn=0, niter=100, nthin=1)
     pred <- ccPred(outdir)

