generateE             package:beadarray             R Documentation

_G_e_n_e_r_a_t_e _E_r_r_o_r _I_m_a_g_e _f_o_r _B_e_a_d_L_e_v_e_l_L_i_s_t _o_b_j_e_c_t

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

     Generates an Error Image from the data in a 'BeadLevelList'
     object.

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

     generateE(BLData, array, neighbours = NULL, log = TRUE, method = "median", what = "residG", bgfilter = "none", invasions = 20)

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

  BLData: 'BeadLevelList'

   array: integer specifying which strip/array to plot

neighbours: A Neighbours matrix. Optional - if left NULL, it will be
          computed.

     log: Logical. If TRUE, compute residuals on the log scale.

  method: Method for computing residuals. Options are '"mean"' and
          '"median"'

    what: What to derive the error image from, as used in
          'getArrayData'.

bgfilter: Method passed to the function 'BGFilter'. Options are "none",
          "mean", "median", "MAD" and "medianMAD".

invasions: Integer - Number of invasions. This argument is passed to
          the function BGfilter.

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

     generateE creates an error image, usually based on bead residuals.
     This output can then be fed into 'BASHDiffuse' or 'BASHExtended'.

     If 'what' is 'residG', 'residR', or 'residM', then residuals are
     calculated based on 'method'. For other values of 'what', the
     residuals are not calculated.

     We then apply a "background filter" to this data, using the
     function 'BGFilter' with arguments 'bgfilter' and 'invasions' -
     see its help file for more details. The background filter
     subtracts an estimate of the local background of the error image,
     and/or scales by the local MAD. This step is disabled by using
     'bgfilter = "none"'.

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

     An "Error Image" - a vector of length equal to the number of beads
     on the array.

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

     Jonathan Cairns

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

     'BGFilter'

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

     data(BLData)
     E <- generateE(BLData,1)
     E <- generateE(BLData,1, invasions = 10) #reduced no of invasions to increase speed.
     E <- generateE(BLData,1, bgfilter = "none") #residuals (median)

