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/* This is an example HY-PHY Batch File.
It reads in a '#' nucleotide dataset data/hiv.nuc and estimates
maximum ln-likelihood based on the tree contained in the data file,
using the General Reversible model with all 6 parameters
estimated independently for all branches.
Output is printed out as a Newick Style tree with branch lengths
representing the number of expected substitutions per branch (which
is the default setting for nucleotide models w/o rate variation).
Sergei L. Kosakovsky Pond and Spencer V. Muse
December 1999.
*/
/* 1. Read in the data and store the result in a DataSet variable.*/
DataSet nucleotideSequences = ReadDataFile ("data/hiv.nuc");
/* 2. Filter the data, specifying that all of the data is to be used
and that it is to be treated as nucleotides.*/
DataSetFilter filteredData = CreateFilter (nucleotideSequences,1);
/* 3. Collect observed nucleotide frequencies from the filtered data. observedFreqs will
store the vector of frequencies. */
HarvestFrequencies (observedFreqs, filteredData, 1, 1, 1);
/* 4. Define the KHY substitution matrix. '*' is defined to be -(sum of off-diag row elements) */
REVRateMatrix =
{{*,a,b,c}
{a,*,d,e}
{b,d,*,f}
{c,e,f,*}};
/*5. Define the REV model, by combining the substitution matrix with the vector of observed (equilibrium)
frequencies. */
Model REV = (REVRateMatrix, observedFreqs);
/*6. Now we can define the tree variable, using the tree string read from the data file,
and, by default, assigning the last defined model (REV) to all tree branches. */
Tree givenTree = DATAFILE_TREE;
/*7. Since all the likelihood function ingredients (data, tree, equilibrium frequencies)
have been defined we are ready to construct the likelihood function. */
LikelihoodFunction theLnLik = (filteredData, givenTree);
/*8. Maximize the likelihood function, storing parameter values in the matrix paramValues */
Optimize (paramValues, theLnLik);
/*9. Print the tree with optimal branch lengths to the console. */
fprintf (stdout, theLnLik);
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