SpikeInExpressionSet-class     package:spkTools     R Documentation

_C_l_a_s_s _t_o _C_o_n_t_a_i_n _a_n_d _D_e_s_c_r_i_b_e _H_i_g_h-_T_h_r_o_u_g_h_p_u_t _E_x_p_r_e_s_s_i_o_n _L_e_v_e_l _A_s_s_a_y_s
_w_i_t_h _S_p_i_k_e-_i_n _D_a_t_a

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

     This is a class representation for spike-in expression data.
     'SpikeInExpressionSet' class is derived from 'ExpressionSet', and
     requires a matrix names 'exprs' and a matrix named 'spikeIn'.

_E_x_t_e_n_d_s:

     Extends class 'ExpressionSet'.

_C_r_e_a_t_i_n_g _O_b_j_e_c_t_s:

     'createSpikeInExpressionSet(exprs, spikeIn, ...)'

     'new("SpikeInExpressionSet", phenoData =
     new("AnnotatedDataFrame"), featureData =
     new("AnnotatedDataFrame"), experimentData = new("MIAME"),
     annotation = character(0), exprs = new("matrix"), spikeIn =
     new("matrix")) '  

     This creates a 'SpikeInExpressionSet' with 'assayData' implicitly
     created to contain 'exprs' and 'spikeIn'. Additional named matrix
     arguments with the same dimensions as 'exprs' are added to
     'assayData'; the row and column names of these additional matrices
     should match those of 'exprs' and 'spikeIn'.

     'new("SpikeInExpressionSet", assayData =
     assayDataNew(exprs=new("matrix"),spikeIn=new("matrix")),  
     phenoData = new("AnnotatedDataFrame"), featureData =
     new("AnnotatedDataFrame"), experimentData = new("MIAME"),
     annotation = character(0), '

     This creates a 'SpikeInExpressionSet' with 'assayData' provided
     explicitly. In this form, the only required named argument is
     'assayData'.

_S_l_o_t_s:

     Inherited from 'ExpressionSet':

     '_a_s_s_a_y_D_a_t_a': Contains matrices with equal dimensions, and with
          column number equal to 'nrow(phenoData)'. 'assayData' must
          contain a matrix 'exprs' and a matrix 'spikeIn' with rows
          representing features and columns representing samples.  

     '_p_h_e_n_o_D_a_t_a': See 'eSet'

     '_a_n_n_o_t_a_t_i_o_n' See 'eSet'

     '_f_e_a_t_u_r_e_D_a_t_a' See 'eSet'

     '_e_x_p_e_r_i_m_e_n_t_D_a_t_a': See 'eSet' 

_M_e_t_h_o_d_s:

     Class-specific methods:

     '_s_p_i_k_e_I_n(_S_p_i_k_e_I_n_E_x_p_r_e_s_s_i_o_n_S_e_t)', '_s_p_i_k_e_I_n(_S_p_i_k_e_I_n_E_x_p_r_e_s_s_i_o_n_S_e_t)<-' 
          Access and set elements named 'spikeIn' in the
          'AssayData-class' slot.

     '_s_p_k_S_p_l_i_t(_S_p_i_k_e_I_n_E_x_p_r_e_s_s_i_o_n_S_e_t)' creates two SpikeInExpressionSet
          objects - one with the spike-in probes and one with the
          non-spike-in probes.

     For derived methods (see 'ExpressionSet').

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

     'eSet-class', 'ExpressionSet-class'.

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

     # create an instance of SpikeInExpressionSet
     new("SpikeInExpressionSet")

     new("SpikeInExpressionSet", exprs=matrix(runif(1000), nrow=100), spikeIn=matrix(rep(1:10,100), nrow=100))

     # class specific methods
     data(affy)
     affySpikes <- spikeIn(affy)
     affySplit <- spkSplit(affy)

