cosieWrapper          package:oneChannelGUI          R Documentation

_A _w_r_a_p_p_e_r _t_o _c_o_s_i_e, _C_o_r_r_e_c_t_e_d _S_p_l_i_c_i_n_g _I_n_d_i_c_e_s _f_o_r _E_x_o_n _a_r_r_a_y_s, _t_h_a_t _f_o_r _a_n_y _g_i_v_e_n _s_e_t _o_f _n_e_w _e_x_o_n _a_r_r_a_y _e_x_p_e_r_i_m_e_n_t_s
_c_o_r_r_e_c_t_s _f_o_r _t_h_e _o_b_s_e_r_v_e_d _b_i_a_s _a_n_d _i_m_p_r_o_v_e_s _t_h_e _d_e_t_e_c_t_i_o_n _o_f _a_l_t_e_r_n_a_t_i_v_e _s_p_l_i_c_i_n_g

_D_e_s_c_r_i_p_t_i_o_n:

     COSIE is a function that for a given set of exon arrays corrects
     for the observed bias and improves  the detection of alternative
     splicing. It adjusts splicing indices for exons, especially for
     those that belong  to differentially expressed genes. For this
     adjustment, COSIE uses parameters that are specific for each
     probeset  which were trained from a large number of published exon
     arrays. The downside of this approach is that such parameters 
     cannot be estimated for all probesets on the microarray. Based on
     our training set, COSIE corrects 95.1 percent  of the probesets.
     Separate parameter files are provided for both the full and core
     sets, including all  probesets that are linked to transcripts. We
     recommend the use of the core set that was also used in the cited
     study below.  The full set is not as well characterized.

_U_s_a_g_e:

     cosieWrapper()

_A_u_t_h_o_r(_s):

     Gaidatzis et al. Nucleic Acids Research, 2009, 1

_S_e_e _A_l_s_o:

     cosieHscore, cosieMmcore, cosieHsfull, cosieMmfull

