applyStickyError        package:simulatorAPMS        R Documentation

_F_u_n_c_t_i_o_n _t_h_a_t _t_a_k_e_s _s_t_i_c_k_y _p_r_o_t_e_i_n_s _a_n_d _c_a_l_c_u_l_a_t_e_s _F_P'_s

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

     This function simulates False Positive (FP) observations on those
     bait proteins known to have affinity towards a large number of
     prey proteins during the AP-MS process.

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

     applyStickyError(notFoundProt, rateSticky)

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

notFoundProt: A character vector of proteins that have no known
          interactions with the bait protein B.

rateSticky: The rate at which bait B attracts other proteins ands
          records FP observations due to its systematic affinity to
          interact with other proteins.

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

     If there is a non-trivial number of sticky bait proteins, the
     function 'runSimulators' calls the intermediary function
     'simulatorS'. This latter function controls 'applyStickyError' by
     examining the arguments and parameters. For each sticky bait,
     'simulatorS' calls this function to generate un-natural
     interactions.

     This is essentially a function for recording more FP interactions
     among baits and non-prey. The function takes in a bait that is
     known to have some high level of finding prey as a result of the
     experimentation.

     In essence, the bait attracts and binds to other proteins with
     which it would normally not interact.

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

     The character vector, ProtInErr:

     The return value, ProtInErr, is a vector consisting of a subset of
     proteins from the set notFoundProt. This subset will be those
     proteins which form systematic FP observations for the simulation.

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

     T. Chiang

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

     'applyFPErrors', 'applyDeformationError'

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

     data(TSNMatrix)
     exampleNotFoundPrey <- rownames(TSNMatrix)[1:50]
     applyStickyError(exampleNotFoundPrey, 0.9)

