aCGH.test                package:aCGH                R Documentation

_T_e_s_t_i_n_g _a_s_s_o_c_i_a_t_i_o_n _o_f _a_C_G_H _c_l_o_n_e_s _w_i_t_h _c_e_n_s_o_r_e_d _o_r _c_o_n_t_i_n_u_o_u_s
_o_u_t_c_o_m_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     'aCGH.test' function tests for association of each clone in an
     univariate manner with censored or continous outcome by fitting
     Cox proportional hazards model or linear regression model. There
     is also an alternative to Cox prop. hazards - testing for
     differences in survival curves defined by the groups in the
     outcome variable using the G^rho family of tests.

_U_s_a_g_e:

     aCGH.test(aCGH.obj, rsp, test = c("survdiff","coxph",
               "linear.regression"), p.adjust.method = "fdr",imputed=TRUE, 
                subset = NULL, strt = NULL, ...)

_A_r_g_u_m_e_n_t_s:

aCGH.obj: aCGH object containing clones' log2 ratios. 

     rsp: Response variable which is either 'Surv' object from
          'survival' package or continous outcome.

    test: Currently only three values are allowed - "coxph",
          "survdiff", and "linear.regression", which test for
          association using Cox proportional hazards model, G^rho
          family of tests ('survdiff') or linear model. 

p.adjust.method: This is a parameter controlling how the p-values from
          the univariate tests are going to be adjusted for multiple
          testing. Default value is Benjamini & Hochberg (1995) FDR
          method. Please refer to 'p.adjust' function for more help.

 imputed: Whether imputed or original log2ratios should be used.
          Default is TRUE (imputed).

  subset: Specifies subset index of clones to be tested.

    strt: Aptional strata variable for splitting the data in different
          strata.

     ...: Optional parameters passed further along to each of the
          univariate testing functions.

_V_a_l_u_e:

     A data frame similar to the result returned from 'mt.maxT'
     function from 'multtest' package with components: 

   index: Vector of row indices, between 1 and 'nrow(X)', where rows
          are sorted first according to their adjusted p-values, next
          their unadjusted p-values, and finally their test statistics. 

teststat: Vector of test statistics, ordered according to 'index'. To
          get the test statistics in the original data order, use
          'teststat[order(index)]'. 

    rawp: Vector of raw (unadjusted) p-values, ordered according to
          'index'. 

    adjp: Vector of adjusted p-values, ordered according to 'index'. 

_A_u_t_h_o_r(_s):

     Peter Dimitrov

_S_e_e _A_l_s_o:

     'aCGH', 'Surv', 'mt.maxT', 'coxph', 'survdiff', 'p.adjust'

_E_x_a_m_p_l_e_s:

