findOutliers             package:snapCGH             R Documentation

_F_u_n_c_t_i_o_n _t_o _i_d_e_n_t_i_f_y _o_u_t_l_i_e_r _c_l_o_n_e_s

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

     The function identified the clones that are outliers.

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

     findOutliers(segList, thres = madGenome, factor = 4)

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

 segList: An object of class 'SegList'

   thres: Estimate of experimental variability, generally, madGenome

  factor: Factor indicating how many standard

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

     The outliers are the clones that are dissimilar enough from the
     clones assigned to the same state. Magnitude of the factor
     determines how many MADs away from a median a value needs to be to
     be declared an outlier. Outliers consitent over many samples may
     indicate technological artificat with that clone or possibly copy
     number polymorpism.

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

 outlier: Binary matrix with a row for each clone and column for each
          sample. "1" indicates outlier, 0 otherwise.

pred.obs.out: Matrix with a row for each clone and column for each
          sample. The entries are the median value for the state with
          outliers exceluded for all clones but outliers. The value if
          the observed value for the outliers.

pred.out: Matrix with a row for each clone and column for each sample.
          The entries are the median value for the state 

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

     Jane Fridlyand

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

     Application of Hidden Markov Models to the analysis of the array
     CGH  data, Fridlyand et.al., _JMVA_, 2004

_S_e_e _A_l_s_o:

     'findGenomicEvents'

