estErrProbMethodOfMoments      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
_b_y _m_e_t_h_o_d _m_o_m_e_n_t_s.

_D_e_s_c_r_i_p_t_i_o_n:

     Estimate false positive and false negative error probabilities by
     method moments.

_U_s_a_g_e:

     estErrProbMethodOfMoments(nint, nrec, nunr, ntot)

_A_r_g_u_m_e_n_t_s:

    nint: Integer vector. True number of interactions. Typically, the
          function is called for a range of these, returning all
          possible solutions for that range.

    nrec: Integer scalar. Observed number of reciprocated edges.

    nunr: Integer scalar. Observed number of unreciprocated edges.

    ntot: Integer scalar. Number of proteins which were tested twice
          (e.g. both as viable bait and as viable prey).

_D_e_t_a_i_l_s:

     The model is described in the vignette _Stochastic and systematic
     errors in PPI data, by looking at unreciprocated in- or out-edges_
     by W. Huber, T. Chiang and R. Gentleman.

_V_a_l_u_e:

     Matrix with 5 columns 'nint' (a copy of the input argument),
     'pfp1', 'pfn1', 'pfp2' and 'pfn2', and as many rows as the length
     of 'nint'.

_A_u_t_h_o_r(_s):

     Wolfgang Huber <URL: http://www.ebi.ac.uk/huber>

_E_x_a_m_p_l_e_s:

     est = estErrProbMethodOfMoments(nint=seq(8000, 40000, by=100), nrec=9722, nunr=15856, ntot=2000)
     if(interactive()) {
       plot(est[, c("pfp2", "pfn2")], type="l", col="blue", lwd=2,
            xlab=expression(p[FP]), ylab=expression(p[FN]))
       abline(h=0, v=0, lty=2)
     }

