deds.stat.linkC             package:DEDS             R Documentation

_D_i_f_f_e_r_e_n_t_a_i_l _E_x_p_r_e_s_s_i_o_n _v_i_a _D_i_s_t_a_n_c_e _S_u_m_m_a_r_y _o_f _M_u_l_t_i_p_l_e _S_t_a_t_i_s_t_i_c_s

_D_e_s_c_r_i_p_t_i_o_n:

     'deds.stat.linkC' integrates different statistics of differential
     expression (DE) to rank and select a set of DE genes.

_U_s_a_g_e:

     deds.stat.linkC(X, L, B = 1000, tests = c("t", "fc", "sam"), tail =
     c("abs", "lower", "higher"), extras = NULL, distance = c("weuclid",
     "euclid"), adj = c("fdr", "adjp"), nsig = nrow(X), quick = TRUE)

_A_r_g_u_m_e_n_t_s:

       X: A  matrix, with m rows corresponding to variables
          (hypotheses) and n columns corresponding to observations. In
          the case of gene expression data, rows correspond to genes
          and columns to mRNA samples. The data can be read using
          'read.table'.

       L: A vector of integers corresponding to observation (column)
          class labels. For k classes, the labels must be integers
          between 0 and k-1.

       B: The number of permutations. For a complete enumeration, 'B'
          should be 0 (zero) or any number not less than the total
          number of permutations.

   tests: A character vector specifying the statistics to be used to
          test the null hypothesis of no association between the
          variables and the class labels, 'test' could be any of the
          following:  

            '"t"':     one or two sample t-statistics;
            '"f"':     F-statistics;
            '"fc"':    fold changes among classes;
            '"sam"':   SAM-statistics;
            '"modt"':  moderated t-statistics;
            '"modt"':  moderated F-statistics;
            '"B"':     B-statistics.

    tail: A character string specifying the type of rejection region.
           If 'side="abs"', two-tailed tests, the null hypothesis is
          rejected for large absolute values of the test statistic.
           If 'side="higher"', one-tailed tests, the null hypothesis is
          rejected for large values of the test statistic.
           If 'side="lower"', one-tailed tests,  the null hypothesis is
          rejected for small values of the test statistic. 

  extras: Extra parameter needed for the test specified; see
          'deds.genExtra'.

distance: A character string specifying the type of distance measure
          used for the calculation of the distance to the extreme point
          (E). 
           If 'distance="weuclid"', weighted euclidean distance, the
          weight for statistic t is 1/MAD(t); 
           If 'distance="euclid"', euclidean distance. 

     adj: A character string specifying the type of multiple testing
          adjustment. 
           If 'adj="fdr"', False Discovery Rate is controled and q
          values are returned. 
           If 'adj="adjp"', ajusted p values that controls family wise
          type I error rate are returned.

    nsig: If 'adj = "fdr"', 'nsig' specifies the number of top
          differentially expressed genes whose q values will be
          calculated; we recommend  setting 'nsig < m', as the
          computation of q values will be extensive. q values for the
          rest of genes will be approximated to 1. If 'adj = "adjp"',
          the  calculation of the adjusted p values will be for the
          whole dataset.

   quick: A logical variable specifying if a quick but memory requiring
          procedure will be selected. If 'quick=TRUE', permutation will
          be carried out once and stored in memory; If 'quick=FALSE' a
          fixed seeded sampling procedure will be employed, which
          requires more computation time as the permutation will be
          carried out twice, but will not use extra memory for storage.

_D_e_t_a_i_l_s:

     'deds.stat.linkC' summarizes multiple statistical measures for the
     evidence of DE. The DEDS methodology treats each gene as a point
     corresponding to a gene's vector of DE measures. An "extreme
     origin" is defined as the maxima of all statistics and the
     distance from all points to the extreme is computed and ranking of
     a gene for DE is determined by the closeness of the gene to the
     extreme. To determine a cutoff for declaration of DE, null
     referent distributions are generated by permuting the data matrix.

     Statistical measures currently in the DEDS package include t
     statistics ('tests="t"'), fold changes ('tests="fc"'), F
     statistics ('tests="f"'), SAM ('tests="sam"'), moderated t
     ('tests="modt"'), moderated F statistics ('tests="modf"'), and B
     statistics ('tests="B"'). The function 'deds.stat.linkC'
     interfaces to C functions for the tests and the computation of
     DEDS. For more flexibility, the user can also use 'deds.stat'
     which has the same functionality as 'deds.stat.linkC' but is
     written completely in R (therefore slower) and the user can supply
     their own function for a statistic not covered in the DEDS
     package.

     DEDS can also summarize p values from different statistical
     models, see 'deds.pval'.

_V_a_l_u_e:

     An object of class 'DEDS'. See 'DEDS-class'.

_A_u_t_h_o_r(_s):

     Yuanyuan Xiao, yxiao@itsa.ucsf.edu, 
      Jean Yee Hwa Yang, jean@biostat.ucsf.edu.

_R_e_f_e_r_e_n_c_e_s:

     Yang, Y.H., Xiao, Y. and Segal M.R.: Selecting differentially
     expressed genes from microarray experiment by sets of statistics.
     _Bioinformatics_ 2005 21:1084-1093.

_S_e_e _A_l_s_o:

     'deds.pval', 'deds.stat'.

_E_x_a_m_p_l_e_s:

     X <- matrix(rnorm(1000,0,0.5), nc=10)
     L <- rep(0:1,c(5,5))

     # genes 1-10 are differentially expressed
     X[1:10,6:10]<-X[1:10,6:10]+1
     # DEDS summarizing t, fc and sam
     d <- deds.stat.linkC(X, L, B=200)

