amova                  package:ade4                  R Documentation

_A_n_a_l_y_s_i_s _o_f _m_o_l_e_c_u_l_a_r _v_a_r_i_a_n_c_e

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

     The analysis of molecular variance tests the differences among
     population and/or groups of populations in a way similar to ANOVA.
     It includes evolutionary distances among alleles.

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

     amova(samples, distances, structures)
     print.amova(x, full = FALSE, ...)

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

 samples: a data frame with haplotypes (or genotypes) as rows,
          populations as columns and abundance as entries

distances: an object of class 'dist' computed from Euclidean distance.
          If 'distances' is null, equidistances are used.

structures: a data frame containing, in the jth row and the kth column,
          the name of the group of level k to which the jth population
          belongs

       x: an object of class 'amova'

    full: a logical value indicating whether the original data
          ('distances','samples','structures') should be printed

     ...: further arguments passed to or from other methods

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

     Returns a list of class 'amova' 

    call: call

 results: a data frame with the degrees of freedom, the sums of
          squares, and the mean squares. Rows represent levels of
          variability.

componentsofcovariance: a data frame containing the components of
          covariance and their contribution to the total covariance

 statphi: a data frame containing the phi-statistics

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

     Sandrine Pavoine pavoine@biomserv.univ-lyon1.fr

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

     Excoffier, L., Smouse, P.E. and Quattro, J.M. (1992) Analysis of
     molecular variance inferred from metric distances among DNA
     haplotypes: application to human mitochondrial DNA restriction
     data. _Genetics_, *131*, 479-491.

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

     'randtest.amova'

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

     data(humDNAm)
     amovahum <- amova(humDNAm$samples, sqrt(humDNAm$distances), humDNAm$structures)
     amovahum

