mergeComplexes           package:apComplex           R Documentation

_I_t_e_r_a_t_i_v_e_l_y _c_o_m_b_i_n_e _c_o_l_u_m_n_s _i_n _i_n_i_t_i_a_l _P_C_M_G _e_s_t_i_m_a_t_e

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

     Repeatedly applies the function 'LCdelta' to make combinations of
     columns in the affiliation matrix representing the protein complex
     membership graph (PCMG) for AP-MS data.

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

     mergeComplexes(PCMG, adjMat, simMat = NULL, sensitivity = 0.75,
     specificity = 0.995, Beta = 0, wsVal=NULL)

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

    PCMG: Current PCMG estimate

  adjMat: Adjacency matrix of bait-hit data from an AP-MS experiment. 
          Rows correspond to baits and columns to hits.

  simMat: An optional square matrix with entries between 0 and 1.  Rows
          and columns correspond to the proteins in the experiment, and
          should be reported in the same order as the columns of
          'adjMat'.  Higher values in this matrix are interpreted to
          mean higher similarity for protein pairs.

sensitivity: Believed sensitivity of AP-MS technology.

specificity: Believed specificity of AP-MS technology.

    Beta: Optional additional parameter for the weight to give data in
          'simMat' in the logistic regression model.

   wsVal: A numeric. This is the value assigned to the work-space in
          the call to fisher.test.

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

     The local modeling algorithm for AP-MS data described by Scholtens
     and Gentleman (2004) and Scholtens, Vidal, and Gentleman
     (submitted) uses a two-component measure of protein complex
     estimate quality, namely P=LxC. Columns in 'cMat' represent
     individual complex estimates.  The algorithm works by starting
     with a maximal BH-complete subgraph estimate of 'cMat', and then
     improves the estimate by combining columns such that P=LxC
     increases.  

     When proposing combinations of columns 'comp1' and 'comp2' in
     'cMat', the proposal is accepted if the output from 'LCdelta' (the
     log of LxC) is greater than zero.   'mergeComplexes' performs all
     column combinations until no more combinations result in an output
     from 'LCdelta' greater than zero.

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

     An affiliation matrix representing the estimated PCMG.  The number
     of rows and the row labels of the matrix will be the same as
     'adjMat'.  The number of columns will be less than or equal to the
     number of columns in 'adjMat'.

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

     Denise Scholtens

_R_e_f_e_r_e_n_c_e_s:

     Scholtens D and Gentleman R.  Making sense of high-throughput
     protein-protein interaction data.  Statistical Applications in
     Genetics and Molecular Biology 3, Article 39 (2004).

     Scholtens D, Vidal M, and Gentleman R.  Local modeling of global
     interactome networks.  Bioinformatics 21, 3548-3557 (2005).

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

     'LCdelta','bhmaxSubgraph','findComplexes'

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

     data(apEX)
     PCMG0 <- bhmaxSubgraph(apEX)
     PCMG1 <- mergeComplexes(PCMG0,apEX,sensitivity=.7,specificity=.75)

