qb.confound              package:qtlbim              R Documentation

_E_x_a_m_i_n_e _c_o_n_f_o_u_n_d_i_n_g _o_f _c_o_v_a_r_i_a_t_e _w_i_t_h _p_s_e_u_d_o_m_a_r_k_e_r_s.

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

     Covariates used in gene mapping may be correlated with covariates.
     These routines examine the pattern of confounding.

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

     qb.confound(qbObject, covar = 1)
     ## S3 method for class 'qb.confound':
     plot(x, ylim, main, ...)
     ## S3 method for class 'qb.confound':
     print(x, ...)
     ## S3 method for class 'qb.confound':
     summary(object, ...)

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

qbObject: Object of class 'qb'.

       x: Object of class 'qb.confound'.

  object: Object of class 'qb.confound'.

   covar: Index to covariate

    ylim: Limits for 'y' (vertical) plotting axis.

    main: Title for plot.

     ...: Additional parameters passed alone.

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

     This examines possible confounding between a covariate and
     pseudomarkers across the genome. Confouding, evidenced by large
     correlation with a marker, would raise suspicions about mapping in
     a genomic region, unless of course the covariate is a marker in
     that region. Blue curves are correlation with additive effect; red
     curves are correlation with dominance effect. Dashed lines at 5
     percent significance limits.

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

     'qb.confound' returns a matrix with columns for: 

  coradd: Correlation with additive pseudomarker effect.

  cordom: Correlation with dominance pseudomarker effect (if F2).

     chr: Chromosome identifier.

     The object inherits from 'scanone' objects.

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

     Brian S. Yandell

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

     http://www.qtlbim.org

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

     'qb.mcmc'

_E_x_a_m_p_l_e_s:

     temp <- qb.confound(qbExample)
     plot(temp)

