rawpCheck           package:oneChannelGUI           R Documentation

_R_a_w _p-_v_a_l_u_e _d_i_s_t_r_i_b_u_t_i_o_n _f_r_o_m _l_i_m_m_a _a_n_a_l_y_s_i_s _b_y _a _m_o_u_s_e _c_l_i_c_k

_D_e_s_c_r_i_p_t_i_o_n:

     This function allow to visualize the histogram of raw p-value
     distribution generated by limma analysis.

_U_s_a_g_e:

     rawpCheck()

_D_e_t_a_i_l_s:

     The histogram of raw p-value distribution will show if raw
     p-values are uniform in the  non significant range and therefore
     the BH correction can be applied.

_N_o_t_e:

     BH is the most used method for the correction of type I errors in
     microarray analysis. However, it has some limitation due to the
     initial hypotheses: The gene expressions are independent from each
     other. The raw distribution of p values should be uniform in the
     non significant range.

_A_u_t_h_o_r(_s):

     Raffaele A Calogero

_R_e_f_e_r_e_n_c_e_s:

     To know more see limma package help

