BGFilter              package:beadarray              R Documentation

_B_a_c_k_g_r_o_u_n_d _F_i_l_t_e_r

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

     Performs various image transforms, based on statistics from local
     beads.

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

     BGFilter(E = NULL, neighbours, invasions = 20, method = "median")

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

       E: Error Image

neighbours: A Neighbours matrix. Required.

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

  method: Method for computing local statistics. Options are
          '"median"', '"mean"', '"MAD"', '"medianMAD"'

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

     This function transforms an error image based on a local
     statistic.

     To obtain our statistic, we use an invasion process. Links between
     beads are defined in the neighbours matrix. We define the local
     beads as those which can be reached in 'invasions' steps from the
     first bead, and then collect their values.

     'method = "median"' subtracts the local median from each error
     intensity.

     'method = "mean"' subtracts the local mean from each error
     intensity.

     'method = "MAD"' divides each bead's intensity by the MAD (median
     absolute devation from the median) of local beads.

     'method = "medianMAD"' subtracts the local median from each error
     intensity, and then divides each intensity by the local MAD.

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

     A vector - the updated error image.

_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,bgfilter = "none")
     neighbours <- generateNeighbours(BLData,1)
     E.MAD <- BGFilter(E, neighbours, method = "MAD")
     E.median <- BGFilter(E, neighbours, method = "median")

