cghRaw                package:CGHbase                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 _r_a_w _o_r _n_o_r_m_a_l_i_z_e_d _a_r_r_a_y _c_o_m_p_a_r_a_t_i_v_e _g_e_n_o_m_i_c _h_y_b_r_i_d_i_z_a_t_i_o_n _d_a_t_a.

_D_e_s_c_r_i_p_t_i_o_n:

     Container for aCGH data and experimental metadata. 'cghRaw' class
     is derived from 'eSet', and requires a matrix named 'copynumber'
     as assayData member. Furthermore, columns named 'Chromosome',
     'Start', and 'End' are required as featureData members, containing
     feature position information.

_E_x_t_e_n_d_s:

     Directly extends class 'eSet'.

_C_r_e_a_t_i_n_g _O_b_j_e_c_t_s:

     'new('cghRaw', phenoData = [AnnotatedDataFrame], experimentData =
     [MIAME], annotation = [character], copynumber = [matrix],
     featureData = [AnnotatedDataFrame], ...) '

     'make_cghRaw' is a function to convert a dataframe or textfile to
     an object of class 'cghRaw'. The input should be either a
     dataframe  or a tabseparated textfile (textfiles must contain a
     header). The first  three columns should contain the name,
     chromosome and position in bp for  each array target respectively.
     The chromosome and position column must  contain numbers only.
     Following these is a column with log2 ratios for  each of your
     samples. If the input type is a textfile, missing values  should
     be represented as 'NA' or an empty field.

_S_l_o_t_s:

     Inherited from 'eSet':

     '_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 'copynumber' with rows represening array
          probes and columns representing samples. Additional matrices
          of identical size (e.g., representing measurement errors) may
          also be included in 'assayData'. Class:'AssayData-class'

     '_p_h_e_n_o_D_a_t_a': See 'eSet'

     '_f_e_a_t_u_r_e_D_a_t_a': An 'AnnotatedDataFrame' with columns 'Chromosome',
          'Start', and 'End' containing array element position  data.

     '_e_x_p_e_r_i_m_e_n_t_D_a_t_a': See 'eSet'

     '_a_n_n_o_t_a_t_i_o_n': See 'eSet'

_M_e_t_h_o_d_s:

     Class-specific methods.

     '_c_o_p_y_n_u_m_b_e_r(_c_g_h_R_a_w)', '_c_o_p_y_n_u_m_b_e_r(_c_g_h_R_a_w,_m_a_t_r_i_x)<-' Access and set
          elements named 'copynumber' in the 'AssayData-class' slot.

     '_c_h_r_o_m_o_s_o_m_e_s', '_b_p_s_t_a_r_t', '_b_p_e_n_d' Access the chromosomal positions
          stored in 'featureData'

     _p_l_o_t._c_g_h_R_a_w Create a plot containing log2ratios ordered by
          chromosomal position

     See 'eSet' for derived methods. Annotation functionality is not
     yet supported.

_A_u_t_h_o_r(_s):

     Sjoerd Vosse

_S_e_e _A_l_s_o:

     'eSet-class', 'cghSeg-class', 'cghCall-class'

_E_x_a_m_p_l_e_s:

             # create an instance of cghRaw
             new("cghRaw")
             
             # create an instance of cghRaw from a dataframe
             data(WiltingData)
             cghobj <- cghRaw(WiltingData)
             
             # plot the first sample
             plot.cghRaw(cghobj[,1])
             # first three chromosomes
             plot.cghRaw(cghobj[chromosomes(cghobj)==1,1])
             
             # get the copynumber values of the third and fourth sample
             log2ratios <- copynumber(cghobj[,3:4])
             
             # get the names of the samples
             sampleNames(cghobj)
             
             # get the names of the array elements
             featureNames(cghobj)

