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<h3>
Saira Hussain pushed to branch master
at <a href="https://salsa.debian.org/med-team/hyphy">Debian Med / hyphy</a>
</h3>
<h4>
Commits:
</h4>
<ul>
<li>
<strong><a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3">a5e8e8cf</a></strong>
<div>
<span>by Saira Hussain</span>
<i>at 2019-07-05T13:19:50Z</i>
</div>
<pre class="commit-message" style="white-space: pre-wrap; margin: 0;">Add the SimpleAnalyses suite for testing
</pre>
</li>
</ul>
<h4>10 changed files:</h4>
<ul>
<li class="file-stats">
<a href="#d4d5292902f97d2d883cb64fcea618ded1d779c4">
<span class="new-file">
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debian/tests/SimpleAnalyses/F81.bf
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</li>
<li class="file-stats">
<a href="#423f26a3fb722d0b71d611743b852e0f9ef06128">
<span class="new-file">
+
debian/tests/SimpleAnalyses/HKY85.bf
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<li class="file-stats">
<a href="#eaaec2c22da4f51eed5f5d0d2aba5c6363663662">
<span class="new-file">
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debian/tests/SimpleAnalyses/HKY85shared.bf
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</a>
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<li class="file-stats">
<a href="#5931c1b702be4164257466c5abc47034ca87063c">
<span class="new-file">
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debian/tests/SimpleAnalyses/JC69.bf
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</li>
<li class="file-stats">
<a href="#087c3b1e8350bb5792d795535fba0ace9919cd5d">
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debian/tests/SimpleAnalyses/K2P.bf
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<a href="#3f177908b2fe8362e5edf22fd5cfe3b0ab9afa4f">
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debian/tests/SimpleAnalyses/K2Pshared.bf
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<li class="file-stats">
<a href="#b5c4b1764c30c09aebc4705cb1b11e24d38e44d1">
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debian/tests/SimpleAnalyses/Non-Rev.bf
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<li class="file-stats">
<a href="#2644c4d343e09621ecad4da89aed5f6ff9dc6a56">
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debian/tests/SimpleAnalyses/REV.bf
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<a href="#18f742728e04a3ed44dce818ac46354758ff2db3">
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debian/tests/SimpleAnalyses/REVshared.bf
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<li class="file-stats">
<a href="#4ae7253318c4f8f955957c287be9957410f1bef6">
<span class="new-file">
+
debian/tests/SimpleAnalyses/data/hiv.nuc
</span>
</a>
</li>
</ul>
<h4>Changes:</h4>
<li id="d4d5292902f97d2d883cb64fcea618ded1d779c4">
<a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3#d4d5292902f97d2d883cb64fcea618ded1d779c4"><strong>debian/tests/SimpleAnalyses/F81.bf</strong></a>
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<td class="diff-line-num new new_line" data-linenumber="1" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">/* 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 Felsenstein 81 model.
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 F81 substitution matrix. '*' is defined to be -(sum of off-diag row elements) */
F81RateMatrix =
{{*,mu,mu,mu}
{mu,*,mu,mu}
{mu,mu,*,mu}
{mu,mu,mu,*}};
/*5. Define the F81 models, by combining the substitution matrix with the vector of observed (equilibrium)
frequencies. */
Model F81 = (F81RateMatrix, 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 (F81) 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);
</span></pre>
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<br>
</li>
<li id="423f26a3fb722d0b71d611743b852e0f9ef06128">
<a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3#423f26a3fb722d0b71d611743b852e0f9ef06128"><strong>debian/tests/SimpleAnalyses/HKY85.bf</strong></a>
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<td class="diff-line-num new old_line" data-linenumber="0" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<td class="diff-line-num new new_line" data-linenumber="1" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">/* 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 Hasegawa et all 85 (HKY 85) model with transition/transversion ratio
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) */
HKY85RateMatrix =
{{*,trvs,trst,trvs}
{trvs,*,trvs,trst}
{trst,trvs,*,trvs}
{trvs,trst,trvs,*}};
/*5. Define the HKY85 model, by combining the substitution matrix with the vector of observed (equilibrium)
frequencies. */
Model HKY85 = (HKY85RateMatrix, 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 (HKY85) 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);
</span></pre>
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<td class="new_line diff-line-num" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #f0f0f0; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#fafafa"></td>
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</table>
<br>
</li>
<li id="eaaec2c22da4f51eed5f5d0d2aba5c6363663662">
<a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3#eaaec2c22da4f51eed5f5d0d2aba5c6363663662"><strong>debian/tests/SimpleAnalyses/HKY85shared.bf</strong></a>
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<td class="diff-line-num new old_line" data-linenumber="0" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<td class="diff-line-num new new_line" data-linenumber="1" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">/* 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 Hasegawa et all 85 (HKY 85) model with transition/transversion ratio
shared by 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).
The variable R is the global transition/transversion ratio. */
global R;
HKY85RateMatrix =
{{*,trvs,R*trvs,trvs}
{trvs,*,trvs,R*trvs}
{R*trvs,trvs,*,trvs}
{trvs,R*trvs,trvs,*}};
/*5. Define the HKY85 model, by combining the substitution matrix with the vector of observed (equilibrium)
frequencies. */
Model HKY85 = (HKY85RateMatrix, 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 (HKY85) 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);
</span></pre>
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<td class="new_line diff-line-num" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #f0f0f0; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#fafafa"></td>
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<br>
</li>
<li id="5931c1b702be4164257466c5abc47034ca87063c">
<a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3#5931c1b702be4164257466c5abc47034ca87063c"><strong>debian/tests/SimpleAnalyses/JC69.bf</strong></a>
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<td class="diff-line-num new new_line" data-linenumber="1" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">/* 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 Jukes Cantor 69 model.
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. Define the F81 substitution matrix. '*' is defined to be -(sum of off-diag row elements) */
JC69RateMatrix =
{{*,mu,mu,mu}
{mu,*,mu,mu}
{mu,mu,*,mu}
{mu,mu,mu,*}};
/*4. Define the F81 models, by combining the substitution matrix with the vector of equal equilibrim
frequencies. */
equalFreqs = {{.25}{.25}{.25}{.25}};
Model F81 = (JC69RateMatrix, equalFreqs);
/*5. Now we can define the tree variable, using the tree string read from the data file,
and, by default, assigning the last defined model (JC69) to all tree branches. */
Tree givenTree = DATAFILE_TREE;
/*6. 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);
/*7. Maximize the likelihood function, storing parameter values in the matrix paramValues */
Optimize (paramValues, theLnLik);
/*8. Print the tree with optimal branch lengths to the console. */
fprintf (stdout, theLnLik);
</span></pre>
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<br>
</li>
<li id="087c3b1e8350bb5792d795535fba0ace9919cd5d">
<a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3#087c3b1e8350bb5792d795535fba0ace9919cd5d"><strong>debian/tests/SimpleAnalyses/K2P.bf</strong></a>
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">/* 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 Kimura 2 parameter model with transition/transversion ratio
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. Define the K2P substitution matrix. '*' is defined to be -(sum of off-diag row elements) */
K2PRateMatrix =
{{*,trvs,trst,trvs}
{trvs,*,trvs,trst}
{trst,trvs,*,trvs}
{trvs,trst,trvs,*}};
/*4. Define the K2P model, by combining the substitution matrix with the vector of equal equilibrium
frequencies. */
equalFreqs = {{.25}{.25}{.25}{.25}};
Model K2P = (K2PRateMatrix, equalFreqs);
/*5. Now we can define the tree variable, using the tree string read from the data file,
and, by default, assigning the last defined model (K2P) to all tree branches. */
Tree givenTree = DATAFILE_TREE;
/*6. 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);
/*7. Maximize the likelihood function, storing parameter values in the matrix paramValues */
Optimize (paramValues, theLnLik);
/*8. Print the tree with optimal branch lengths to the console. */
fprintf (stdout, theLnLik);
</span></pre>
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<li id="3f177908b2fe8362e5edf22fd5cfe3b0ab9afa4f">
<a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3#3f177908b2fe8362e5edf22fd5cfe3b0ab9afa4f"><strong>debian/tests/SimpleAnalyses/K2Pshared.bf</strong></a>
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">/* 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 Kimura 2 parameter model with shared transition/transversion ratio
accross 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. Define the K2P substitution matrix. '*' is defined to be -(sum of off-diag row elements)
The variable R is the global transition/transversion ratio. */
global R;
K2PRateMatrix =
{{*,mu,R*mu,mu}
{mu,*,mu,R*mu}
{R*mu,mu,*,mu}
{mu,R*mu,mu,*}};
/*4. Define the K2P model, by combining the substitution matrix with the vector of equal equilibrium
frequencies. */
equalFreqs = {{.25}{.25}{.25}{.25}};
Model K2P = (K2PRateMatrix, equalFreqs);
/*5. Now we can define the tree variable, using the tree string read from the data file,
and, by default, assigning the last defined model (K2P) to all tree branches. */
Tree givenTree = DATAFILE_TREE;
/*6. 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);
/*7. Maximize the likelihood function, storing parameter values in the matrix paramValues */
Optimize (paramValues, theLnLik);
/*8. Print the tree with optimal branch lengths to the console. */
fprintf (stdout, theLnLik);
</span></pre>
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<li id="b5c4b1764c30c09aebc4705cb1b11e24d38e44d1">
<a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3#b5c4b1764c30c09aebc4705cb1b11e24d38e44d1"><strong>debian/tests/SimpleAnalyses/Non-Rev.bf</strong></a>
<hr>
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</td>
<td class="diff-line-num new new_line" data-linenumber="1" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">/* 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 non-reversible 12 parameter (with 3 constraints)
model. The tree from the data file is unrooted.
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
November 2002.
*/
/* 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 12 parameter non-reversible substitution matrix.
The constraints on some of the substitution rates are necessary to
ensure that observed nucleotide frequencies are equilibrium
frequencies for the model.
'*' is defined to be -(sum of off-diag row elements) */
/* frequency ratios */
r0 = observedFreqs[0]/observedFreqs[3];
r1 = observedFreqs[1]/observedFreqs[3];
r2 = observedFreqs[2]/observedFreqs[3];
/* All the global rate parameters are defined relative to
the rate for A->C. For instance, CG represents the ratio
of the rates C->G/A->C. */
global AG;
global AT;
global CA;
global CG;
global CT;
global GA;
global GC;
global GT;
/* note that these constraints are
satisfied if we restrict the model to the
general reversible case */
global TA:=AT+(1-CA)*r1__+(AG-GA)*r2__;
global TC:=CT+(CA-1)*r0__+(CG-GC)*r2__;
global TG:=GT+(GA-AG)*r0__+(GC-CG)*r1__;
NRRateMatrix =
{{*,t,t*AG,t*AT}
{t*CA,*,t*CG,t*CT}
{t*GA,t*GC,*,t*GT}
{t*TA,t*TC,t*TG,*}};
/*5. Define the Non-Rev model, by combining the substitution matrix with the vector of observed (equilibrium)
frequencies. */
Model NRM = (NRRateMatrix, 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 (NRM) 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);
</span></pre>
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<td class="new_line diff-line-num" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #f0f0f0; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#fafafa"></td>
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</table>
<br>
</li>
<li id="2644c4d343e09621ecad4da89aed5f6ff9dc6a56">
<a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3#2644c4d343e09621ecad4da89aed5f6ff9dc6a56"><strong>debian/tests/SimpleAnalyses/REV.bf</strong></a>
<hr>
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<td class="diff-line-num new new_line" data-linenumber="1" style="width: 35px; color: rgba(0,0,0,0.3); border-right-width: 1px; border-right-color: #c7f0d2; border-right-style: solid; padding: 0 5px;" align="right" bgcolor="#ddfbe6">
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">/* 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);
</span></pre>
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</tr>
</table>
<br>
</li>
<li id="18f742728e04a3ed44dce818ac46354758ff2db3">
<a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3#18f742728e04a3ed44dce818ac46354758ff2db3"><strong>debian/tests/SimpleAnalyses/REVshared.bf</strong></a>
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">/* 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 the parameters
shared by 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).
AG,AT,CG,CT,GT are the shared parameters, representing the ratio
of corresponding substitution rates to the AC rate.
t is the "branch length"*/
global AG;
global AT;
global CG;
global CT;
global GT;
REVRateMatrix =
{{*,t,AG*t,AT*t}
{t,*,CG*t,CT*t}
{AG*t,CG*t,*,GT*t}
{AT*t,CT*t,GT*t,*}};
/*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);
</span></pre>
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<br>
</li>
<li id="4ae7253318c4f8f955957c287be9957410f1bef6">
<a href="https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3#4ae7253318c4f8f955957c287be9957410f1bef6"><strong>debian/tests/SimpleAnalyses/data/hiv.nuc</strong></a>
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<pre style="margin: 0;">+<span id="LC1" class="line" lang="plaintext">#719
ATAGTAATTAGATCTGAAAACTTCTCGAACAATGCTAAAACCATAATAGTACAGCTAAAT
AAATCTGTAGAAATTAATTGTACAAGACCCAACAACAATACAAGAAGAAGTATACAT
TTCGGACCAGGGAAAGCATTTTATGCAGGAGAAATAATAGGAGATATAAGACAAGCA
TATTGTACTCTTAATGGAGCAGAATGGAATAACACTGTAAAACAGGTAGCTGCAAAATTA
AGAGAAAAATTTAATAAAACAATAATCTTTAATCAATCC
#136
GTAGTAATTAGATCTGAAAACTTCTCGAACAATGCTAAAACCATAATAGTACAGCTAAAT
AAATCTGTAGAAATTAATTGTACAAGACCCAACAACAATACAAGAAGAAGTATACAT
TTTGGACCAGGGAAAGCATTTTATGCAGGAGAAATAATAGGAGATATAAGACAAGCA
TATTGTACCCTTAATGGAACAGAATGGAATAACACTTTAAAACAGGTAGCTGAAAAATTA
AGAGAACAATTTATTAAAACAATAGTTTTTAATCAATCC
#135
GTAGTAATTAGATCTGAAAACTTCACGAACAATGCTAAAACCATAATAGTACAGCTAAAT
AAATCTGTAGAAATTAATTGTGTAAGACCCGGCAACAATACAAGAAGAAGTATACAT
ATAGGACCAGGGAGAGCATATTATACAGGAGAAGTAATAGGAGATATAAGACAAGCA
CATTGTAACCTTAGTAGAACAGACTGGAATAAAACTTTAAAACAGGTAGCTGAAAAATTA
AGAGAACAATTTAATACAACAATAGTCTTTAATCAATCC
#105r
ATAGTAATTAGATCTGAAAACTTCACGAACAATGCTAAAACCATAATAGTACAGCTAAAT
AAATCTGTAGAAATTAAGTGTGAAAGACCCAACAACAATACAAGAAAAAGTGTACAT
ATAGGACCAGGGAAAGCATATTATACAGGAGAAATAATAGGAGATATAAGACAAGCA
CATTGTAACCTTAGTGGAACAGAATGGAGGGAAACTTTAAAACAGGTAGCTGAAAAATTA
AGAGAACAATTTAATAAAACAATAGTCTTTAATCAATCC
#529
ATAGTAATTAGATCTGAAAACTTCACGAACAATGCTAAAACCATAATAGTACATCTAAAT
GAATCTGTAGAAATTATTTGTGAAAGACCCAACAACAATACAAGAAAAAGTGTACAT
ATGGGACCAGGGAGAGCATATTACACAGGAGAAATAATAGGAGATATAAGACAAGCA
CATTGTAACATTAGTAGAACAAATTGGACGGAAACTTTAAAACAGGTAGCTGAAAAATTA
AGAGAACAATTTAATAAAACAATAGTCTTTAATCAATCC
#317
GTAGTAATTAGATCTGAAAACTTCACGAACAATGCTAAGACCATAATAGTACAGCTAAAT
AAACCTGTAAAAATTAATTGTACAAGACCCAACAACAATGCAAAAATAAGAATACAT
ATAGGACCAGGGAGACCATTTTATACAGCAGGAGAAATAGGAAATATAAGACAAGCA
CATTGTAACCTTAGTAGAACAGACTGGAATAACACTTTAAAACTGGTAGCTGAAAAATTA
AGAGAACAATTTAATAAAACAATAGTCTTTAATCAATCC
#6767
GTAGTAATTAGATCTGAAAACTTCACGAACAATGCTAAGACCATAATAGTACAGCTAAAT
AACTCTGTAACAATTAAGTGTGAAAGACCCAACAACAATACAAGAAAAAGTATACCT
ATAGGACCAGGGAGAGCCTTTTATACAACAGGAGACATAGGAGATATAAGACAAGCA
CATTGTAACCTTAGTAGAAAAGACTGGAATGACACTTTAAGACAGGTAGTTGGAAAGTTA
AGAGAACAATTTGGAAGAACAATAATCTTTAATCAATCC
#6760
ATAGTAATTAGATCTGAAAACTTCACGAACAATGCTAAAACCATAATAGTACAGCTAAAG
GAACCTGTAAACATTACTTGTGAAAGACCCAGCAACAATACAAGAAAAAGTATACAT
ATAGGACCAGGAAAAGCATTTTATGCAACAGGAGAAATAGGAGATATAAGACGAGCA
CATTGTAACCTTAATAGAACAGCATGGAATAAAACTTTAAAACAGGTAGTTGAAAAATTA
AGAGAACAATTTAAGAAAACAATAACCTTTAACCAATCC
#9939
ATAGTAATCAGATCTGAAAACTTCTCGGACAATGCTAAAACCATAATAGTACAGCTAAAC
AACACTGTAAACATTACTTGTGAAAGACCCAACAACAATACAAGAAAAAGGATACAT
ATAGGACCAGGGAGAGCAGTTTATACAACAGGACAAATAGGAGATATAAGAAAAGCA
CATTGTAACCTTAGTAGAACAAATTGGACTGAAACTTTAAGACAAGTAGCTGAAAAATTA
AAAGAACAATTTAATAAAACAATAATCTTTAATAATTCC
#113
GTAGTAATTCGATCTGAAAACTTCACGGACAATGCTAAAACCATAATAGTACAGCTAAAC
AAATCTGTAGAAATTACTTGTGTAAGACCCAACAACAATACAAGAAAAAGTATAAAT
ATAAGACCAGGGAGAGCATTTTATACAACAGGAGAAATAGGAGATATAAGACAAGCA
CATTGTAACCTTAGTAGAACAGCATGGAATGAAGCTTTAAGACAAGTAGCTAAAAAATTA
AAAGAACAATTTAATAGAACAATAGTCTTTAATCAATCC
#822
ATAGTAATTAGATCTGAAAACTTCACAGACAATGCTAAAACCATAATAGTACAGCTAAAC
AAATCTGTAGAAATTAATTGTATAAGACCCAACAACAATACAAGAAAAAGTATACAT
ATAGGACCAGGGAGAGCATTTTATACAACAGGAGACATAGGAGATATAAGACAAGCA
TATTGTAACCTTAGTAGAACAGCATGGAATGAAACTTTAAGACAAGTAGCTCAAAAATTA
AAAGAACAATTTAATAGAACAATAGTCTTTAATCAATCC
#159
ATAGTAATTAGATCTGAAAACTTCACAGACAATGCTAAAACCATAATAGTACAGCTAAAT
AAATCTGTAGAAATTAATTGTACAAGACCCAACAACAATACAAGAAAAAGTATACAT
ATAGGACCAGGGAGAGCTTTTTATACAACAGGTGAAATAGGAGATTTAAGACAAGCA
CATTGTAACCTTAGTAGAACAGCATGGAATGAAACTTTAAGACAAGTAGCTAAAAAATTA
AAAGAACAATTTAATAGAACAATAGTTTTTAATCAATCC
#256
ATAGTAATTAGATCTGAAAACTTCACGGACAATGCTAAAACCATAATAGTACAGCTAAAT
AAATCTGTAGAAATTAATTGTACAAGACCCAACAACAATACAAGAAAAAGTATAAAT
ATAGGACCAGGGAGAGCATTTTATACAACAGGTGAAATAGGAAATTTAAGACAAGCA
CATTGTAACCTTAGTAGAACAGCATGGAATGAAACTTTAAGACAAGTAGCTAAAAAACTA
AAAGAACAATTTAATAGAACAATAGTTTTTAATCAATCC
(((317,6767),((135,(529,105r)),(719,136))),6760,((113,9939),(256,(822,159))))</span></pre>
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