do.aGFF.calc              package:ACME              R Documentation

_P_e_r_f_o_r_m _A_C_M_E _c_a_l_c_u_l_a_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     This function performs the moving window chi-square calculation. 
     It is written in C, so is quite fast.

_U_s_a_g_e:

     do.aGFF.calc(x, window, thresh)

_A_r_g_u_m_e_n_t_s:

       x: An 'aGFF' class object

  window: An integer value, representing the number of basepairs to
          include in the windowed chi-square calculation

  thresh: The quantile of the data distribution for each sample that
          will be used to classify a probe as positive

_D_e_t_a_i_l_s:

     A window size on the order of 2-3 times the average size of
     fragments from sonication, digestion, etc. and containing at least
     8-10 probes is the recommended size.  Larger size windows are
     probably more sensitive, but obviously reduce the accuracy with
     which boundaries of signal can be called.

     A threshold of between 0.9 and 0.99 seems empirically to be
     adequate. If one plots the histogram of data values and there is
     an obvious better choice (such as a bimodal distribution, with one
     peak representing enrichment), a more data-driven approach may
     yield better results.

_V_a_l_u_e:

     An object of class 'aGFFCalc'

_A_u_t_h_o_r(_s):

     Sean Davis <sdavis2@mail.nih.gov>

_E_x_a_m_p_l_e_s:

     data(example.agff)
     example.agffcalc <- do.aGFF.calc(example.agff,window=1000,thresh=0.9)
     example.agffcalc

