[med-svn] [Git][med-team/hyphy][master] Add the SimpleAnalyses suite for testing
Saira Hussain
gitlab at salsa.debian.org
Fri Jul 5 14:20:02 BST 2019
Saira Hussain pushed to branch master at Debian Med / hyphy
Commits:
a5e8e8cf by Saira Hussain at 2019-07-05T13:19:50Z
Add the SimpleAnalyses suite for testing
- - - - -
10 changed files:
- + debian/tests/SimpleAnalyses/F81.bf
- + debian/tests/SimpleAnalyses/HKY85.bf
- + debian/tests/SimpleAnalyses/HKY85shared.bf
- + debian/tests/SimpleAnalyses/JC69.bf
- + debian/tests/SimpleAnalyses/K2P.bf
- + debian/tests/SimpleAnalyses/K2Pshared.bf
- + debian/tests/SimpleAnalyses/Non-Rev.bf
- + debian/tests/SimpleAnalyses/REV.bf
- + debian/tests/SimpleAnalyses/REVshared.bf
- + debian/tests/SimpleAnalyses/data/hiv.nuc
Changes:
=====================================
debian/tests/SimpleAnalyses/F81.bf
=====================================
@@ -0,0 +1 @@
+/* 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);
\ No newline at end of file
=====================================
debian/tests/SimpleAnalyses/HKY85.bf
=====================================
@@ -0,0 +1 @@
+/* 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);
\ No newline at end of file
=====================================
debian/tests/SimpleAnalyses/HKY85shared.bf
=====================================
@@ -0,0 +1 @@
+/* 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);
\ No newline at end of file
=====================================
debian/tests/SimpleAnalyses/JC69.bf
=====================================
@@ -0,0 +1 @@
+/* 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);
\ No newline at end of file
=====================================
debian/tests/SimpleAnalyses/K2P.bf
=====================================
@@ -0,0 +1 @@
+/* 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);
\ No newline at end of file
=====================================
debian/tests/SimpleAnalyses/K2Pshared.bf
=====================================
@@ -0,0 +1 @@
+/* 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);
\ No newline at end of file
=====================================
debian/tests/SimpleAnalyses/Non-Rev.bf
=====================================
@@ -0,0 +1 @@
+/* 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);
\ No newline at end of file
=====================================
debian/tests/SimpleAnalyses/REV.bf
=====================================
@@ -0,0 +1 @@
+/* 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);
\ No newline at end of file
=====================================
debian/tests/SimpleAnalyses/REVshared.bf
=====================================
@@ -0,0 +1 @@
+/* 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);
\ No newline at end of file
=====================================
debian/tests/SimpleAnalyses/data/hiv.nuc
=====================================
@@ -0,0 +1 @@
+#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))))
\ No newline at end of file
View it on GitLab: https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3
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View it on GitLab: https://salsa.debian.org/med-team/hyphy/commit/a5e8e8cf91a6606172216c325923710d44f52ee3
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