topgenes                package:DEDS                R Documentation

_T_a_b_l_e _o_f _T_o_p _G_e_n_e_s _f_r_o_m _D_E_D_S

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

     'topgenes' prints a table of top-ranked genes by 'DEDS'.

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

     topgenes(obj, number = 10, genelist = NULL, sort.by = c("deds", colnames(obj$stats[,-1])), tail = c("abs", "lower", "higher"))

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

     obj: An object of 'DEDS'

  number: A numeric variable specifying the number of top genes to be
          printed out.

genelist: A dataframe or a vector containing gene names.

 sort.by: A character string specifying the name of the statistic to
          sort genes by. The default uses the DEDS result, the user can
          also choose from the names of the statistics (or unadjusted p
          values) that DEDS is used to summarize.

    tail: A character string specifying the type of rejection region.
           If 'side="abs"', two-tailed tests, genes are ranked by their
          absolute values. 
           If 'side="higher"', one-tailed tests, genes are ranked
          decreasingly. 
           If 'side="lower"', one-tailed tests, genes are ranked
          increasingly.

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

     The function 'topgenes' accepts a 'DEDS' object as the first
     argument. The 'DEDS' class is a simple list-based class to store
     DEDS results. The list contains a "stat" component, which stores
     statistics or unadjusted p-values from various statistical tests.
     The function 'topgenes.DEDS' extracts the "stat" component and
     prints out the top genes according to the user defined criterion -
     usually by DEDS or by a single statistical measure that DEDS
     summarizes.

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

     A dataframe with rows for selected genes, and columns for the
     "stat" matrix and q- or adjusted p-values from DEDS.

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

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

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

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

_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)

     # top table, ranked by DEDS
     topgenes(d)
     # top table, ranked by t
     topgenes(d, sort.by="t")

