selectStats            package:goCluster            R Documentation

_S_e_l_e_c_t_s _r_e_l_e_v_a_n_t _a_n_n_o_t_a_t_i_o_n _t_e_r_m_s

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

     This function removes all annotation terms with a p-value higher
     than the given threshold from the given tree.

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

     selectStats(X, threshold)

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

       X: The tree of annotation terms as retrieved by the statistical
          analysis function (e.g. evalClusterHyper)

threshold: The selection threshold for the p-values. 

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

     The function will walk through all nodes of the tree specified as
     X and removes all annotation terms with a p-value lower than the
     given threshold. The resulting tree will have the same structure
     as before but it can contain nodes that  are empty. This function
     does perform no correction for multiple testing whatsoever and
     should be used with caution.

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

     A reduced tree with annotation elements having a "significant"
     p-value.

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

     Gunnar Wrobel, <URL: work@gunnarwrobel.de>, <URL:
     http://www.gunnarwrobel.de>.

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

     'clusterSignifBase-class'

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

     set.seed(1000)

     data(benomylsetupsmall)

     a <- new("goCluster")

     execute(a) <- benomylsetupsmall

     ## The statistics are saved in the "statset" slot of
     ## the "stat" object that is itself a child of the "sign"
     ## object of a "goCluster" object
     ## We select all items with a p-value below 0.05 here. 
     selectStats(a@sign@stat@statset,0.05)

