normalize              package:CGHcall              R Documentation

_N_o_r_m_a_l_i_z_a_t_i_o_n _a_n_d _c_e_l_l_u_l_a_r_i_t_y _a_d_j_u_s_t_m_e_n_t _f_o_r _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 normalizes arrayCGH data using the global mode or
     median. It can also adjust for the cellularity of your data.

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

     normalize(input, type = "dataframe", method = "median", cellularity = 1, smoothOutliers = TRUE, ...)

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

   input: Either the name of a file or a dataframe. See details for the
          format. 

    type: What kind of data format is used as input? Either 'dataframe'
          or 'file'. 

  method: Normalization method, either 'median', 'mode', or 'none'. 

cellularity: A vector of cellularities ranging from 0 to 1 to define
          the contamination of your sample with healthy cells (1 = no
          contamination). See details for more information. 

smoothOutliers: Logical. Indicates whether outliers should be smoothed
          using the 'smooth.CNA' function.

     ...: Arguments for 'smooth.CNA'. 

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

     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.

     The cellularity parameter should be a vector of length n where n
     is the number of samples in your dataset. The vector is recycled
     if there are not enough values in it, or truncated if there are
     too many. For more information on the correction we refer to
     section 1.6 of the supplementary information for van de Wiel et
     al. 2006.

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

     This function returns a dataframe in the same format as the input
     with normalized and/or cellularity adjusted log2 ratios.

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

     Sjoerd Vosse & Mark van de Wiel

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

       data(Wilting)
       ## First preprocess the data
       raw.data <- preprocess(Wilting, type="dataframe")
       ## Simple global median normalization for samples with 75% tumor cells
       perc.tumor <- rep(0.75, 3)
       normalized.data <- normalize(raw.data, cellularity=perc.tumor)

