qvalue                package:qvalue                R Documentation

_E_s_t_i_m_a_t_e _t_h_e _q-_v_a_l_u_e_s _f_o_r _a _g_i_v_e_n _s_e_t _o_f _p-_v_a_l_u_e_s

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

     Estimate the q-values for a given set of p-values.  The q-value of
     a test measures the proportion of false positives incurred (called
     the false discovery rate) when that particular test is called
     significant.

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

     qvalue(p=NULL, lambda=seq(0,0.90,0.05), pi0.method="smoother", fdr.level=NULL, robust=FALSE, gui=FALSE, 
       smooth.df=3, smooth.log.pi0=FALSE)

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

       p: A vector of p-values (only necessary input)

  lambda: The value of the tuning parameter to estimate pi_0. Must be
          in [0,1). Optional, see Storey (2002).

pi0.method: Either "smoother" or "bootstrap"; the method for
          automatically choosing tuning parameter in the estimation of
          pi_0,  the proportion of true null hypotheses

fdr.level: A level at which to control the FDR. Must be in (0,1].
          Optional; if this is selected, a vector of TRUE and FALSE is
          returned that specifies whether each q-value is less than
          fdr.level or not.

  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. Optional.

     gui: A flag to indicate to 'qvalue' that it should communicate
          with  the gui.  Should not be specified on command line.
          Optional.

smooth.df: Number of degrees-of-freedom to use when estimating pi_0 
          with a smoother. Optional.

smooth.log.pi0: If TRUE and \texttt{pi0.method} = "smoother", pi_0 will
          be  estimated by applying a smoother to a scatterplot of
          \textit{log} pi_0 estimates  against the tuning parameter
          lambda. Optional.

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

     If no options are selected, then the method used to estimate pi_0
     is the smoother method described in Storey and Tibshirani (2003).
     The bootstrap method is described in Storey, Taylor & Siegmund
     (2004).

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

     A list containing: 

    call: 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 jstorey@u.washington.edu

_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.

     Storey JD and Tibshirani R. (2003) Statistical significance for
     genome-wide experiments. Proceedings of the National Academy of
     Sciences,  100: 9440-9445. 

     Storey JD. (2003) The positive false discovery rate: A Bayesian
     interpretation and the q-value. Annals of Statistics, 31:
     2013-2035.  

     Storey JD, Taylor JE, and Siegmund D. (2004) Strong control,
     conservative point estimation, and simultaneous conservative
     consistency of false discovery rates: A unified approach. Journal
     of the Royal Statistical Society, Series B, 66: 187-205.

     QVALUE Manual <URL:
     http://faculty.washington.edu/~jstorey/qvalue/manual.pdf>

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

     'qplot', 'qwrite', 'qsummary', 'qvalue.gui'

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

     ## Not run: 
     p <- scan("pvalues.txt")
     qobj <- qvalue(p)
     qplot(qobj)
     qwrite(qobj, filename="myresults.txt")

     qobj <- qvalue(p, lambda=0.5, robust=TRUE)
     qobj <- qvalue(p, fdr.level=0.05, pi0.method="bootstrap")
     ## End(Not run)

