spatial                package:MANOR                R Documentation

_E_x_a_m_p_l_e_s _o_f  _a_r_r_a_y-_C_G_H _d_a_t_a _w_i_t_h _s_p_a_t_i_a_l _a_r_t_i_f_a_c_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     This data set provides an example of array-CGH data with spatial
     artifacts, consisting of including 'arrayCGH' objects before and
     after normalization

_U_s_a_g_e:

     data(spatial)

_F_o_r_m_a_t:

_e_d_g_e, _g_r_a_d_i_e_n_t 'arrayCGH' objects before normalization:

         'arrayValues'  spot-level information
         'arrayDesign'  block design of the array
         'cloneValues'  additionnal clone-level data (chromosome, position)


_e_d_g_e._n_o_r_m, _g_r_a_d_i_e_n_t._n_o_r_m 'arrayCGH' objects after normalization 

_D_e_t_a_i_l_s:

     'edge' presents local spatial bias in the top-right edge corner,
     and 'gradient' presents global spatial trend. 'edge' and
     'gradient' are 'arrayCGH' objects before normalization. They have
     been created respectively from spot and gpr files using 'import'.
     'edge.norm' and 'gradient.norm' are the corresponding 'arrayCGH'
     objects after normalization using 'norm.arrayCGH'.

     'flag' objects used for data normalization come from 'flags'
     dataset.

_N_o_t_e:

     People interested in tools for array-CGH analysis can visit our
     web-page: <URL: http://bioinfo.curie.fr>.

_A_u_t_h_o_r(_s):

     Pierre Neuvial, manor@curie.fr.

_S_o_u_r_c_e:

     Institut Curie, manor@curie.fr.

_S_e_e _A_l_s_o:

     'flags'

_E_x_a_m_p_l_e_s:

     data(spatial)

     ## edge: example of array with local spatial effects

     layout(matrix(1:4, 2, 2), height=c(9,1))
     arrayPlot(edge, "LogRatio", main="Log-ratios before normalization",
     zlim=c(-1,1), bar="h", layout=FALSE, mediancenter=TRUE)
     arrayPlot(edge.norm, "LogRatioNorm", main="Log-ratios after spatial
     normalization", zlim=c(-1,1), bar="h", layout=FALSE, mediancenter=TRUE) 

     ## gradient: example of array with spatial gradient

     layout(matrix(1:4, 2, 2), height=c(9,1))
     arrayPlot(gradient, "LogRatio", main="Log-ratios before normalization",
     zlim=c(-2,2), bar="h", layout=FALSE)
     arrayPlot(gradient.norm, "LogRatioNorm", main="Log-ratios after spatial
     normalization", zlim=c(-2,2), bar="h", layout=FALSE)   

