pa.calls                package:panp                R Documentation

_P_r_e_s_e_n_c_e-_A_b_s_e_n_c_e _C_a_l_l_s _f_r_o_m _N_e_g_a_t_i_v_e _S_t_r_a_n_d _M_a_t_c_h_i_n_g _P_r_o_b_e_s_e_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Function to make gene presence/absence calls based on distance
     from empirical distribution of chip-specific negative strand
     matching probesets (NSMP).

_U_s_a_g_e:

     pa.calls(object, looseCutoff = 0.02, tightCutoff = 0.01, verbose = FALSE)

_A_r_g_u_m_e_n_t_s:

  object: an ExpressionSet object (result of running
          expression-generating function, like expresso(), rma(),
          mas5(), etc.) Currently, this must be of chip type HGU133A or
          HGU133 Plus 2.0

looseCutoff: the larger P-value cutoff (see details)

tightCutoff: the smaller, more strict P-value cutoff

 verbose: logical. If 'TRUE' detailed progress messages are reported.

_D_e_t_a_i_l_s:

     The function calculates a matrix of P-values for the expression
     values in the input ExpressionSet. P-values are calculated based
     on the empirical survivor function (1-CDF) of the set of negative
     probesets identified by Affymetrix as negative strand matching
     probesets (NSMP) with no cross hybridization. These probesets are
     therefore assumed to show nothing but background/machine noise
     plus some occasional non-specific binding. The P-value returned
     for any probeset expression value in ExpressionSet is the value of
     the NSMP survivor function for that expression level. 

     Presence/Absence calls are derived by applying the two cutoff
     values to the matrix of P-values for all genes in the
     ExpressionSet, as follows:

     *  Present ('P'):    P-values <= tightCutoff

     *  Absent ('A'):     P-values > looseCutoff

     *  Marginal ('M'):   P-values between tightCutoff and looseCutoff

_V_a_l_u_e:

    list: a new list containing two matrices: Pcalls and Pvals, as
          follows:

 Pcalls : a matrix of Presence (P), Marginal (M), Absent (A) indicators

  Pvals : a matrix of P-values. Each data point is the P-value for the
          expr  at the same x,y coordinates. 

_N_o_t_e:

     NSMP sets have been established for the HGU133A and
     HGU133-Plus-2.0 chipsets to date. Hence only these two are
     currently supported by PANP.

_A_u_t_h_o_r(_s):

     Peter Warren

_R_e_f_e_r_e_n_c_e_s:

     Warren, P., Bienkowska, J., Martini, P., Jackson, J., and Taylor,
     D., PANP - a New Method of Gene Detection on Oligonucleotide
     Expression Arrays (2007), in preparation

_E_x_a_m_p_l_e_s:

     ## Load example ExpressionSet 
     data(gcrma.ExpressionSet)

     ## Generate Pvals and Pcalls matrices from ExpressionSet, using default cutoffs
     PA <- pa.calls(gcrma.ExpressionSet)

     ## to access the Pcalls and Pvals:
     myPcalls <- PA$Pcalls
     myPvals <-  PA$Pvals

