]> 3.6a2 dnadist - Compute distance matrix from nucleotide sequences &phylip_header; dnadist dnadist perl "dnadist < params" 0 infile Alignment File perl "ln -s $infile infile; " -10 12 readseq_ok_alig perl 1 dnadist_opt dnadist options distance Distance (D) F84 1 F84 F84 K Kimura 2-parameter JC Jukes-Cantor LogDet LogDet Similarity Similarity table F84 K "D\\n" JC "D\\nD\\n" LogDet "D\\nD\\nD\\n" Similarity "D\\nD\\nD\\nD\\n" params ratio Transition/transversion ratio (T) perl ($value && $value != $vdef)? "T\\n$value\\n" : "" 2.0 1 params perl $distance eq "F84" || $distance eq "K" gamma Gamma distributed rates across sites (G) 0 5 0 No 1 Yes GI Gamma+Invariant 0 1 "G\\n" GI "G\\nG\\n" params perl $distance eq "F84" || $distance eq "K" || $distance eq "JC" variation_coeff Coefficient of variation of substitution rate among sites (must be positive) (if Gamma) perl ($value)? "$value\\n" : "" 1010 params perl $gamma In gamma distribution parameters, this is 1/(square root of alpha) invariant_sites Fraction of invariant sites (if Gamma) perl ($value)? "$value\\n" : "" 1011 params perl $gamma eq "GI" empirical_frequencies Use empirical base frequencies (F) 1 perl ($value)? "" : "F\\n" 1 params base_frequencies Base frequencies for A, C, G, T/U (if not empirical) (separated by commas) perl "" 2 perl ($base_frequencies =~ s/,/ /g ) && 0 perl ! $empirical_frequencies categ_opt Categories options The alignment file MUST contain a C on the first line and the description of the categories of each site on the following line. Here is a toy example of a file of 5 species with 12 sites, and 2 different categories (first 2 lines): 5 12 C CATEGORIES 111111222222 one_category One category of substitution rates (C) perl (! $one_category)? "C\\n$n_categ\\n$categ_rates\\n" : "" 1 3 params perl $distance eq "F84" || $distance eq "K" || $distance eq "JC" n_categ Number of categories (1 to 9) perl "" 2 there must be no more than 9 categories perl $value > 9 there must be at least one category perl $value < 1 perl ! $one_category categ_rates Rate for each category (separated by commas) perl "" 3 perl ($categ_rates =~ s/,/ /g ) && 0 perl ! $one_category weight_opt Weight options weights Use weights for sites (W) perl ($value)? "W\\n" : "" 1 params weights_file Weights file perl ($value)? "ln -s $weights_file weights; " : "" -1 perl $weights bootstrap Bootstrap options seqboot Perform a bootstrap before analysis perl ($value)? "seqboot < seqboot.params && mv outfile infile &&" : "" 0 -5 By selecting this option, the bootstrap will be performed on your sequence file. So you don't need to perform a separated seqboot before. Don't give an already bootstrapped file to the program, this won't work! method Resampling methods bootstrap 1 bootstrap Bootstrap jackknife Delete-half jackknife permute Permute species for each character permute "J\\nJ\\n" bootstrap "" jackknife "J\\n" 1. The bootstrap. Bootstrapping was invented by Bradley Efron in 1979, and its use in phylogeny estimation was introduced by me (Felsenstein, 1985b). It involves creating a new data set by sampling N characters randomly with replacement, so that the resulting data set has the same size as the original, but some characters have been left out and others are duplicated. The random variation of the results from analyzing these bootstrapped data sets can be shown statistically to be typical of the variation that you would get from collecting new data sets. The method assumes that the characters evolve independently, an assumption that may not be realistic for many kinds of data. 2. Delete-half-jackknifing. This alternative to the bootstrap involves sampling a random half of the characters, and including them in the data but dropping the others. The resulting data sets are half the size of the original, and no characters are duplicated. The random variation from doing this should be very similar to that obtained from the bootstrap. The method is advocated by Wu (1986). 3. Permuting species within characters. This method of resampling (well, OK, it may not be best to call it resampling) was introduced by Archie (1989) and Faith (1990; see also Faith and Cranston, 1991). It involves permuting the columns of the data matrix separately. This produces data matrices that have the same number and kinds of characters but no taxonomic structure. It is used for different purposes than the bootstrap, as it tests not the variation around an estimated tree but the hypothesis that there is no taxonomic structure in the data: if a statistic such as number of steps is significantly smaller in the actual data than it is in replicates that are permuted, then we can argue that there is some taxonomic structure in the data (though perhaps it might be just a pair of sibling species). perl $seqboot seqboot.params seqboot_seed Random number seed (must be odd) perl "$value\\n" 1000 Random number seed must be odd perl $value <= 0 || (($value % 2) == 0) perl $seqboot seqboot.params replicates How many replicates perl ($value && $value != $vdef)? "R\\n$value\\n" : "" 100 1 this server allows no more than 1000 replicates perl $replicates > 1000 perl $seqboot seqboot.params output Output options matrix_form Lower-triangular distance matrix (L) perl ($value)? "L\\n" : "" 0 1 params printdata Print out the data at start of run (1) perl ($value)? "1\\n" : "" 0 1 params outfile outfile phylip_dist perl 1 params params confirm perl "y\\n" 1000 params terminal_type perl "0\\n" -1 params multiple_dataset perl "M\\nD\\n$replicates\\n" 1 perl $seqboot params seqboot_confirm perl "y\\n" 100 perl $seqboot seqboot.params seqboot_terminal_type perl "0\\n" -1 perl $seqboot seqboot.params tmp_params *.params