misinherits            package:snpMatrix            R Documentation

_F_i_n_d _n_o_n-_M_e_n_d_e_l_i_a_n _i_n_h_e_r_i_t_a_n_c_e_s _i_n _f_a_m_i_l_y _d_a_t_a

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

     For SNP data in families, this function locates all subjects whose
     parents are in the dataset and tests each SNP for non-Mendelian
     inheritances in these trios.

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

     misinherits(ped, id, father, mother, data = sys.parent(), snp.data)

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

     ped: Pedigree identifiers

      id: Subject identifiers

  father: Identifiers for subjects' fathers

  mother: Identifiers for subjects' mothers

    data: A data frame in which to evaluate the previous four arguments

snp.data: An object of class '"snp.matrix"' containing the SNP
          genotypes to be tested

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

     The first four arguments are usually derived from  a "pedfile". If
     a  data frame is supplied for the 'data' argument, the first four
     arguments will be evaluated in this frame. Otherwise they will be
     evaluated  in the calling environment. If the arguments are
     missing, they will be  assumed to be in their usual positions in
     the pedfile data frame  i.e. in columns one to four.  If the
     pedfile data are obtained from a dataframe, the row names of the
     'data' and 'snp.data' files will be used to align the pedfile and
     SNP data. Otherwise, these vectors will be assumed to be in the
     same order as the rows of 'snp.data'.

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

     A logical matrix. Rows are subjects with any non-Mendelian
     inheritances and columns are SNPs with any non-Mendelian
     inheritances. The body of the matrix details whether each subject
     has non-Mendelian inheritance at each SNP. If a subject has no
     recorded genotype for a specific SNP, the corresponding element of
     the output matrix is set to NA.

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

     David Clayton david.clayton@cimr.cam.ac.uk

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

     'tdt.snp'

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

     data(families)
     tdt.snp(data=pedfile, snp.data=genotypes)

