PLMset-class             package:affyPLM             R Documentation

_C_l_a_s_s _P_L_M_s_e_t

_D_e_s_c_r_i_p_t_i_o_n:

     This is a class representation for Probe level Linear Models
     fitted to Affymetrix GeneChip probe level data.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created using the function 'fitPLM'

_S_l_o_t_s:

     '_p_r_o_b_e._c_o_e_f_s': Object of class "matrix". Contains model
          coefficients related to probe effects

     '_s_e._p_r_o_b_e._c_o_e_f_s': Object of class "matrix". Contains standard
          error estimates for the probe coefficients  

     '_c_h_i_p._c_o_e_f_s': Object of class "matrix". Contains model
          coefficients related to chip (or chip level) effects for each
          fit.

     '_s_e._c_h_i_p._c_o_e_f_s': Object of class "matrix". Contains standard error
          estimates for the chip coefficients

     '_m_o_d_e_l._d_e_s_c_r_i_p_t_i_o_n': Object of class "character". This string
          describes the probe level model fitted.

     '_w_e_i_g_h_t_s': Object of class "matrix". Contains probe weights for
          each fit. The matrix has columns for chips and rows are
          probes

     '_p_h_e_n_o_D_a_t_a': Object of class "phenoData" This is an instance of
          class 'phenoData'  containing the patient (or case) level
          data. The columns of the pData slot of this entity represent
          variables and the rows represent patients or cases. 

     '_a_n_n_o_t_a_t_i_o_n' A character string identifying the annotation that
          may be used for the 'exprSet' instance.

     '_d_e_s_c_r_i_p_t_i_o_n': Object of class "MIAME". For compatibility with
          previous version of this class description can also be a
          "character". The class 'characterOrMIAME' has been defined
          just for this.

     '_c_d_f_N_a_m_e': A character string giving the name of the cdfFile

     '_n_r_o_w': Object of class "numeric". Number of rows in chip

     '_n_c_o_l': Object of class "numeric". Number of cols in chip

     '_n_o_t_e_s': Object of class "character" Vector of explanatory text 

     '_v_a_r_c_o_v': Object of class "list". A list of variance/covariance
          matrices

     '_r_e_s_i_d_u_a_l_S_E': Object of class "matrix". Contains residual standard
          error and df

     '_r_e_s_i_d_u_a_l_s': Object of class "matrix". Contains residuals from
          model fit (if stored)

_E_x_t_e_n_d_s:

     Class '"exprSet"', directly.

_M_e_t_h_o_d_s:

     _w_e_i_g_h_t_s<- 'signature(object = "PLMset")': replaces the weights 

     _w_e_i_g_h_t_s 'signature(object = "PLMset")': extracts the model fit
          weights

     _c_o_e_f_s<- 'signature(object = "PLMset")': replaces the chip coefs.  

     _c_o_e_f_s 'signature(object = "PLMset")': extracts the chip coefs. 

     _s_e 'signature(object = "PLMset")': extracts the standard error
          estimates of the chip coefs. 

     _s_e<- 'signature(object = "PLMset")': replaces the standard error
          estimates of the chip coefs. 

     _c_o_e_f_s._p_r_o_b_e 'signature(object = "PLMset")': extracts the probe
          coefs. 

     _s_e._p_r_o_b_e 'signature(object = "PLMset")': extracts the standard
          error estimates of the probe coefs.     

     _c_o_e_f_s._c_o_n_s_t 'signature(object = "PLMset")': extracts the intercept
          coefs. 

     _s_e._c_o_n_s_t 'signature(object = "PLMset")': extracts the standard
          error estimates of the intercept coefs. 

     _g_e_t_C_d_f_I_n_f_o 'signature(object = "PLMset")': retrieve the
          environment that defines the location of probes by probe set. 

     _i_m_a_g_e 'signature(x = "PLMset")': creates an image of the robust
          linear model fit weights for each sample.

     _i_n_d_e_x_P_r_o_b_e_s 'signature(object = "PLMset", which = "character")':
          returns a list with locations of the probes in each probe 
          set. The list names defines the probe set names. 'which' can
          be "pm", "mm", or "both". If "both" then perfect match
          locations are given followed by mismatch locations.

     _M_b_o_x 'signature(object = "PLMset")': gives a boxplot of M's for
          each chip. The M's are computed relative to a "median" chip.

     _n_o_r_m_v_e_c will return the normalization vector (if it has been
          stored)

     _r_e_s_i_d_S_E will return the residual SE (if it has been stored)

_N_o_t_e:

     This class is better described in the vignette.

_A_u_t_h_o_r(_s):

     B. M. Bolstad bolstad@stat.berkeley.edu

_E_x_a_m_p_l_e_s:

