estimatePPIErrorRates        package:ppiStats        R Documentation

_E_s_t_i_m_a_t_e _f_a_l_s_e _p_o_s_i_t_i_v_e _a_n_d _f_a_l_s_e _n_e_g_a_t_i_v_e _e_r_r_o_r _p_r_o_b_a_b_i_l_i_t_i_e_s
_f_o_r _d_i_r_e_c_t _p_r_o_t_e_i_n _i_n_t_e_r_a_c_t_i_o_n_s

_D_e_s_c_r_i_p_t_i_o_n:

     Estimate false positive and false negative error probabilities for
     direct protein interactions using a protein interaction graph gold
     standard

_U_s_a_g_e:

     estimatePPIErrorRates(matList,GSPos=NULL,GSNeg=NULL)

_A_r_g_u_m_e_n_t_s:

 matList: A named list of list. The names corresponds to a particular
          publication. Each element of the top list is a list of two
          matrices: 1. The adjacency matrix of the positive interaction
          datapoints. 2. The adjacency matrix of the tested interaction
          datapoints. The dimension names of these two matrices should
          be identical (an error will be thrown if this is not the
          case) where the rows are indexed by the bait proteins and the
          columns are indexed by the prey. The adjacency matrices are
          0,1 matrices where an 1 entry signifies either a positive
          interaction relationship or a positive tested relationship. A
          0 entry is then well defined.

   GSPos: A positive gold standard protein interaction graph given by
          its adjacency matrix. The dimension names of this matrix must
          be the same identifying system used for the dimension names
          for the matrices found within the matList parameter. An entry
          of one in this matrix indicates a positive interaction while
          an entry of zero is inconclusive.

   GSNeg: A negative gold standard protein interaction graph given by
          its adjacency matrix. The dimension names of this matrix must
          be the same identifying system used for the dimension names
          for the matrices found within the matList parameter. An entry
          of one in this matrix indicates a negative interaction while
          an entry of zero is inconclusive.

_D_e_t_a_i_l_s:

     The model is described in the manuscript _Estimating node degree
     in bait-prey graphs._ by D. Scholtens et al.

_V_a_l_u_e:

     A matrix.

     The return value is an kx2 matrix where k is the length of
     matList. The first colum returns the estimated false positive
     error rates and the second column returns the estimated false
     negative error rates.

_A_u_t_h_o_r(_s):

     T. Chiang and L. Wang

_R_e_f_e_r_e_n_c_e_s:

     Scholtens D, Chiang T, Huber W, Gentleman R.  Estimating node
     degree in bait-prey graphs. _Bioinformatics_.

_E_x_a_m_p_l_e_s:

     load(system.file("extdata", "intacty2hppMatrix.rda", package="ppiStats"))
     load(system.file("extdata", "PPIpos", package="ppiStats"))
     x = intacty2hppMatrix[c("EBI-389903","EBI-783101")]
     estimatePPIErrorRates(x, GSPos=PPIpos)

