maxchi               package:stepwise               R Documentation

_S_t_e_p_w_i_s_e _d_e_t_e_c_t_i_o_n _o_f _r_e_c_o_m_b_i_n_a_t_i_o_n _b_r_e_a_k_p_o_i_n_t_s _u_s_i_n_g _M_a_x_C_h_i

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

     Stepwise detection of recombination breakpoints using the maximum
     chi-square (MaxChi) method at each step

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

     maxchi(input_file, breaks, winHalfWidth, permReps)

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

input_file: character string indicating the name of a Phylip format
          data input file

  breaks: an integer vector of ordered site(s) just before the
          previously declared breakpoints

winHalfWidth: the window half width to use

permReps: the number of Monte Carlo replicates to use for the
          permutation distribution

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

     The maxchi function implements the maximum chi-square (MaxChi)
     method for detecting recombination breakpoints (Maynard Smith
     1992) using a moving window of fixed width.  Breakpoints detected
     in previous steps of a stepwise search may be conditioned upon. 

     For a given position of the moving window on the sequence
     alignment, and for a given pair of sequences, a chi-square
     statistic is computed to compare two proportions: the proportion
     of sites at which the sequences agree in the left half-window and
     the proportion of sites in at which the sequences agree in the
     right half-window. Discordance between the two proportions may
     reflect a recombination event, located at the window centre, in
     the history of the two sequences. The maximum chi-square over all
     sequence pairs is regarded as a summary of the evidence for
     recombination at the window centre. The individual chi-square
     statistics may also be of interest for suggesting pairs of
     sequences segments that descend from historical recombination
     events. Significance of observed chi-square statistics is assessed
     by a Monte Carlo permutation test. When conditioning on
     breakpoints proposed at previous steps of a stepwise search,
     permutation is restricted to sites within blocks defined by the
     previously proposed breakpoints, as described by Graham et al.
     (2004).

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

polyposn: The site numbers of all ungapped polymorphic sites in the
          alignment

  chisqs: Observed chi-square statistics that exceed the 90th
          percentile of the permutation null distribution  

 winlocs: Window centres corresponding to the chi-square statistics in
          'chisqs' 

pairmem1: First member of each pair that lead to a significant
          chi-square statistic in 'chisqs' 

pairmem2: Second member of each pair 

  quants: 90th and 95th percentiles of the permutation distribution 

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

     Brad McNeney <mcneney@stat.sfu.ca>, Jinko Graham
     <jgraham@stat.sfu.ca>, Sigal Blay <sblay@sfu.ca>

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

     Graham J, McNeney B and Seillier-Moiseiwitsch F (2004). Stepwise
     detection of  recombination breakpoints in sequence alignments.
     _Bioinformatics_ Sep 23;  [Epub ahead of print]

     Maynard Smith J (1992). Analyzing the mosaic structure of genes.
     _J Mol Evol_, *34*:126-129.

     <URL: http://stat-db.stat.sfu.ca/stepwise>

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

     'summary.maxchi', 'phylpro'

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

      demo(maxchi) 

