SRBCT              package:plsgenomics              R Documentation

_G_e_n_e _e_x_p_r_e_s_s_i_o_n _d_a_t_a _f_r_o_m _K_h_a_n _e_t _a_l. (_2_0_0_1)

_D_e_s_c_r_i_p_t_i_o_n:

     Gene expression data (2308 genes for 83 samples) from the
     microarray experiments of Small Round Blue Cell Tumors (SRBCT)  of
     childhood cancer study of Khan et al. (2001).

_U_s_a_g_e:

     data(SRBCT)

_D_e_t_a_i_l_s:

     This data set contains 83 samples  with 2308 genes: 29 cases of
     Ewing sarcoma (EWS), coded 1,  11 cases of Burkitt lymphoma (BL),
     coded 2, 18 cases of  neuroblastoma (NB), coded 3, 25 cases of
     rhabdomyosarcoma (RMS), coded 4. A total of 63 training samples
     and 25 test samples are  provided in Khan et al. (2001). Five of
     the test set are non-SRBCT and are not considered here. The
     training sample indexes correspond to 1:65 and the test sample
     indexes (without non-SRBCT sample) correspond to 66:83.

_V_a_l_u_e:

     A list with the following elements: 

       X: a (88 x 2308) matrix giving the expression levels of 2308 
          genes for 88 SRBCT patients. Each row corresponds to a
          patient, each column to a gene.

       Y: a numeric vector of length 88 giving the cancer class of each
          patient.

gene.names: a matrix containing the names of the 2308 genes for the
          gene expression matrix 'X'. The two columns correspond to the
          gene 'Image.Id.' and 'Gene.Description', respectively.

_S_o_u_r_c_e:

     The data are described in Khan et al. (2001) and can be freely
     downloaded from  <URL:
     http://www.thep.lu.se/pub/Preprints/01/lu_tp_01_06_supp.html>.

_R_e_f_e_r_e_n_c_e_s:

     Khan, J. and Wei, J. S. and Ringner, M. and Saal, L. H. and
     Ladanyi, M. and Westermann, F. and Berthold, F. and Schwab, M. and
     Antonescu, C. R. and Peterson, C. and Meltzer, P. S. (2001).
     Classification and diagnostic prediction of cancers using gene
     expression profiling and artificial neural networks, Nature
     Medecine, 7, 673-679.

_E_x_a_m_p_l_e_s:

     # load plsgenomics library
     library(plsgenomics)

     # load data set
     data(SRBCT)

     # how many samples and how many genes ?
     dim(SRBCT$X)

     # how many samples of class 1, 2, 3 and 4, respectively ?
     sum(SRBCT$Y==1)
     sum(SRBCT$Y==2)
     sum(SRBCT$Y==3)
     sum(SRBCT$Y==4)

