microsatt                package:ade4                R Documentation

_G_e_n_e_t_i_c _R_e_l_a_t_i_o_n_s_h_i_p_s _b_e_t_w_e_e_n _c_a_t_t_l_e _b_r_e_e_d_s _w_i_t_h _m_i_c_r_o_s_a_t_e_l_l_i_t_e_s

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

     This data set gives genetic relationships between cattle breeds
     with microsatellites.

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

     data(microsatt)

_F_o_r_m_a_t:

     'microsatt' is a list of 4 components. 

     _t_a_b contains the allelic frequencies for 18 cattle breeds (taurine
          or zebu,french or african) and 9 microsatellites.

     _l_o_c_i._n_a_m_e_s is a vector of the names of loci.

     _l_o_c_i._e_f_f is a vector of the number of alleles per locus.

     _a_l_l_e_l_e_s._n_a_m_e_s is a vector of the names of alleles.

_S_o_u_r_c_e:

     Extract of data prepared by D. Laloe ugendla@dga2.jouy.inra.fr
     from data used in:

     Moazami-Goudarzi, K., D. Laloe, J. P. Furet, and F. Grosclaude.
     1997. Analysis of genetic relationships between 10 cattle breeds
     with 17 microsatellites. _Animal Genetics_, *28*, 338-345.

     Souvenir Zafindrajaona, P.,Zeuh V. ,Moazami-Goudarzi K., Laloe D.,
     Bourzat D., Idriss A., and Grosclaude F. (1999) Etude du statut
     phylogntique du bovin Kouri du lac Tchad  l'aide de marqueurs
     molculaires. _Revue d'Elevage et de Mdecine Vtrinaire des pays
     Tropicaux_, *55*, 155-162.

     Moazami-Goudarzi, K., Belemsaga D. M. A., Ceriotti G., Laloe D. ,
     Fagbohoun F., Kouagou N. T., Sidib I., Codjia V., Crimella M. C.,
     Grosclaude F. and Tour S. M. (2001)
      Caractrisation de la race bovine Somba  l'aide de marqueurs
     molculaires. _Revue d'Elevage et de Mdecine Vtrinaire des pays
     Tropicaux_, *54*, 1-10.

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

     ## Not run: 
     data(microsatt)
     fac <- factor(rep(microsatt$loci.names, microsatt$loci.eff))
     w <- dudi.coa(data.frame(t(microsatt$tab)), scann = FALSE)
     wit <- within(w, fac, scann = FALSE)
     microsatt.ktab <- ktab.within(wit)

     plot(sepan(microsatt.ktab)) # 9 separated correspondence analyses
     plot(mcoa(microsatt.ktab, scan = FALSE))
     plot(mfa(microsatt.ktab, scan = FALSE))
     plot(statis(microsatt.ktab, scan = FALSE))
     ## End(Not run)

