preprocess              package:CGHcall              R Documentation

_P_r_e_p_r_o_c_e_s_s _a_r_r_a_y_C_G_H _d_a_t_a

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

     This function preprocesses your aCGH data so it can be processed
     by other functions without errors.

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

     preprocess(input, maxmiss = 30, nchrom = 22, ...)

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

   input: Object of class 'cghRaw'. 

 maxmiss: Maximum percentage of missing values per row. 

  nchrom: Number of chromosomes. 

     ...: Arguments for 'impute.knn' from the impute package. 

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

     This function performs the following actions on arrayCGH data:

        *  Filter out data with missing position information.

        *  Remove data on chromosomes larger than nchrom.

        *  Remove rows with more than maxmiss percentage missing
           values.

        *  Imputes missing values using the 'impute.knn' function from
           the impute package.

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

     This function returns a dataframe in the same format as the input
     with missing values imputed.

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

     Sjoerd Vosse & Mark van de Wiel

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

     Olga Troyanskaya, Michael Cantor, Gavin Sherlock, Pat Brown,
     Trevor Hastie, Robert Tibshirani, David Botstein, and Russ B.
     Altman (2001). Missing value estimation methods for DNA
     microarrays. _Bioinformatics, 17_, 520-525.

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

       data(WiltingRaw)
       preprocessed <- preprocess(WiltingRaw)

