qvalue                package:webbioc                R Documentation

_E_s_t_i_m_a_t_e _p_F_D_R _q-_v_a_l_u_e_s _f_r_o_m _p-_v_a_l_u_e_s

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

     Applies the q-value multiple testing procedure to a group of
     unadjusted p-values.

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

     qvalue(p, lambda=seq(0,0.95,0.05), pi0.meth="smoother", fdr.level=NULL, robust=F)

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

       p: a vector of p-values

fdr.level: a level at which to control the FDR

  lambda: the value of the tuning parameter to estimate pi0

pi0.meth: either "smoother" or "bootstrap"; the method for
          automatically choosing tuning parameter in the estimation of
          pi0, the proportion of true null hypotheses

  robust: an indicator of whether it is desired to make the estimate
          more robust for small p-values and a direct finite sample
          estimate of pFDR

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

    call: gives the function call

     pi0: an estimate of the proportion of null p-values

 qvalues: a vector of the estimated q-values (the main quantity of
          interest)

 pvalues: a vector of the original p-values

significant: if fdr.level is specified, and indicator of whether the
          q-value fell below fdr.level (taking all such q-values to be
          significant controls FDR at level fdr.level)

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

     John D. Storey <URL: http://faculty.washington.edu/~jstorey/>

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

     Storey JD. (2002) A direct approach to false discovery rates.
     _Journal of the Royal Statistical Society_, Series B, 64: 479-498.

