getMeasureRepAgreement       package:cellHTS2       R Documentation

_M_e_a_s_u_r_e_s _o_f _a_g_r_e_e_m_e_n_t _b_e_t_w_e_e_n _p_l_a_t_e _r_e_p_l_i_c_a_t_e_s _f_r_o_m _a _c_e_l_l_H_T_S _o_b_j_e_c_t

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

     Calculate the agreement between plate replicates using raw data or
     normalized data stored in a  'cellHTS' object.  This function
     calculates the repeatability standard deviation between replicate
     plates and the correlation coefficient between replicates. If
     there are more than 2 replicates, the minimum and maximum
     correlation between replicates is given. These measures are
     calculated only for 'sample' wells.

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

     getMeasureRepAgreement(x, corr.method = "spearman")

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

       x: a configured 'cellHTS' object. See details.

corr.method: a character string indicating which correlation
          coefficient should be computed. Can be either "pearson",
          "kendall" or "spearman" (default). The correlation is
          calculated by calling the function  'cor'.

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

     Given an already configured 'cellHTS' object
     ('state(x)[["configured"]]=TRUE'), this function calculates the
     repeatability standard deviation between replicate plates and the
     correlation coefficient between plate replicates using only the
     'sample' wells. If there are more than 2 replicates, the minimum
     and maximum correlation value between pairs of replicates are
     given.

     These measures are calculated using the data values stored in slot
     'assayData' of the 'x'.

     For a given plate p, the repeatability standard deviation is
     determined as the square root of the average of  the squared
     standard deviations (sr) calculated for each sample well k by
     considering the measurement of all of the replicates:


            RepStDev_{p} = sqrt{frac{sum{sr^2}}{n_{k} } }


     where n_{k} is the total number of sample probes for plate p.

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

     The function generates a list with elements: 

     "repStDev": matrix with the calculated repeatability standard
     deviation between plate replicates. It has dimensions 'nrPlates x
     nrChannels';

     "corrCoef" (if the number of replicates equals 2): matrix with the
     correlation coefficients between plate replicates. It has
     dimensions: 'nrPlates x nrChannels';

     "corrCoef.min" (if the number of replicates is greater than 2):
     matrix with the minimum value of the correlation coefficients
     between plate replicates. It has dimensions 'nrPlates x
     nrChannels';

     "corrCoef.max" (if the number of replicates is greater than 2):
     matrix with the maximum value of the correlation coefficients
     between plate replicates. It has dimensions 'nrPlates x
     nrChannels'.

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

     Ligia Bras ligia@ebi.ac.uk

_R_e_f_e_r_e_n_c_e_s:

     Boutros, M., Bras, L.P. and Huber, W. (2006) Analysis of
     cell-based RNAi screens, _Genome Biology_ *7*, R66.

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

     'configure',  'writeReport'

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

         data(KcViabSmall)
         repAgree <- getMeasureRepAgreement(KcViabSmall)
         x <- normalizePlates(KcViabSmall, scale="multiplicative", log=FALSE, method="median", varianceAdjust="none")
         repAgree <- getMeasureRepAgreement(x)

