consistentFilters       package:oneChannelGUI       R Documentation

_T_h_i_s _f_u_n_c_t_i_o_n _a_l_l_o_w_s _f_i_l_t_e_r_i_n_g _u_s_i_n_g _t_h_e _c_o_m_b_i_n_a_t_i_o_n _o_f _m_u_l_t_i_p_l_e _p_a_r_a_m_e_n_t_e_r_s, _e._g. _M_i_D_A_S _p-_v_a_l_u_e_s _a_n_d _R_a_n_k _P_r_o_d_u_c_t _p-_v_a_l_u_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     This filter can be used to moderate multiple tests errors. E.g.
     finding the intersection between MiDAS p-values and Rank Product
     p-values user will remove some of the false positive produced by
     the two methods. A filter on the size of delta Splice Index
     associated to MiDAS p-values filter  will will allow to remove
     statistical significant splicing events which are characterized by
     a very limited variation.

_U_s_a_g_e:

     consistentFilters()

_N_o_t_e:

     This fuction needs the presence of Splice Index data, MiDAS
     p-values and RP p-values. It works for two groups only

_A_u_t_h_o_r(_s):

     Raffaele A Calogero

_S_e_e _A_l_s_o:

     erankProdAltSpl, AptMidas

