minimizeSelection         package:goCluster         R Documentation

_R_e_d_u_c_e_s _t_h_e _l_e_a_v_e_s _o_f _a _t_r_e_e _t_o _m_i_n_i_m_a_l _p-_v_a_l_u_e_s

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

     Given a tree that holds significant annotation terms for a number
     of clusters, the function will reduce the selection of annotation
     terms in each node to the one with minimal p-value.

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

     minimizeSelection(X, annotations)

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

       X: The tree of selected, significant annotations terms. 

annotations: The number of annotations present in the tree. 

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

     The tree, reduced to the annotation terms with minimal 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:

     'clusterVisualHclust-class'

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

     namedv1 <- c(0.01,0.1)
     names(namedv1) <- c("GeneA", "GeneB")
     namedv2 <- c(0.01,0.01)
     names(namedv2) <- c("GeneB", "GeneC")
     namedv3 <- c(0.5,0.1)
     names(namedv3) <- c("GeneD", "GeneE")

     a <- list(annotationA = namedv1,
               annotationB = namedv2,
               annotationC = namedv3)
     b <- list(list(a,a),list(a,a))

     minimizeSelection(a,3)

     minimizeSelection(b,3)

