Either I am missing something, or there is no way to use datasets with some repeat length measurements omitted.

Hello, I want to use haploid data (Y microsatellites) for EBSP analysis.
however I cannot find how to set the ploidy.
Also, I tried to use the template provided by the vntr package but Beauti only works with the standard template to accept the data (csv file) to generate an xml file.
any assistance is greatly appreciated.
best,
eugenia

@arjun-1 The last citation has wrong DOI which is the DOI of the first one:

@Citation(value = 
  "Raazesh Sainudiin et al. (2004) Microsatellite Mutation Models.\n" +
  "  Genetics 168:383-395", year = 2004, firstAuthorSurname = "sainudiin")
@Citation(value =
  "Chieh-Hsi Wu and  Alexei J. Drummond. (2011) Joint Inference of\n" +
  "  Microsatellite Mutation Models, Population History and Genealogies\n" + 
  "  Using Transdimensional Markov Chain Monte Carlo.\n" + 
  "  Genetics 188:151-164",
  DOI= "10.1534/genetics.103.022665", year = 2011, firstAuthorSurname = "wu")

I created the correct citations below, if you like to use:

@Citation(value = 
  "Raazesh Sainudiin et al. (2004) Microsatellite Mutation Models.\n" +
  "  Genetics 168:383-395", 
  DOI= "10.1534/genetics.103.022665", year = 2004, firstAuthorSurname = "Sainudiin")

https://doi.org/10.1534/genetics.103.022665

@Citation(value =
  "Chieh-Hsi Wu and  Alexei J. Drummond. (2011) Joint Inference of\n" +
  "  Microsatellite Mutation Models, Population History and Genealogies\n" + 
  "  Using Transdimensional Markov Chain Monte Carlo.\n" + 
  "  Genetics 188:151-164",
  DOI= "10.1534/genetics.110.125260", year = 2011, firstAuthorSurname = "Wu")

https://doi.org/10.1534/genetics.110.125260

Hi Arjun,

Just to let you know that ant is failing with an error when I attempt to complile due to an "unmappable character" in a citation for several source files. This is what I'm getting:

[javac] /bg01/homescinet/j/jmoncalv/ssanchez/BEASTvntr/src/beast/evolution/substitutionmodel/SainudiinVanilla.java:42: error: unmappable character for encoding ASCII
[javac] " Genetics 168:383???395", year = 2004, firstAuthorSurname = "sainudiin")

I solved it by replacing the "???" character for a '-' in each source file.

Cheers,
Santiago

When importing csv data as multiple partition, each digit is parsed as a column, hence when there are integers with different number of digits in the same column, it throws an error because sequences have different length. For example, if locus1 has allele 1 in the first row and allele 10 in the second, the second will be imported as 1,0.

I'm trying to determine the feasibility of including a strict molecular clock in my BEAST analysis. Right now, I don't see anything on your package to include a temporal (year) aspect within. Is this a possibility with this type of analysis? Or do microsatellite loci not have sufficient information to estimate rates among branches?

Dear Arjun Dhawan,

This is my first time with BEASTvntr. I am having many troubles getting mydata set running.
First, I get a messsage "WARNING: Frequencies has wrong size. Expected 34, but got 4". I do not know how to fix this.
And the analyses crashes with this message "Likelihood incorrectly calculated".
You can see the whole message below.
Please, let me know how to contact you to send you the files. This is my email [email protected]

Any thought could be helpful.
Thanks!
Cheers,
Marcial

File: helodes.xml seed: 1585830943910 threads: 1
Loading package bModelTest v1.2.1
Loading package SA v2.0.2
Loading package SNAPP v1.5.0
Loading package starbeast2 v0.15.5
Loading package BEASTvntr v0.1.3
Loading package MM v1.1.1
Loading package BEAST v2.6.2
Loading package BEASTLabs v1.9.2
Loading package BEAST v2.6.2
Alignment(mydata3aa)
70 taxa
33 sites
33 patterns

WARNING: Frequencies has wrong size. Expected 34, but got 4. Will change now to correct dimension and assume uniform distribution for initial values.
Using BEAGLE version: 3.2.0 (PRE-RELEASE) resource 0: CPU
with instance flags: PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_SSE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU
Using ambiguities in tree likelihood.
Ignoring character uncertainty in tree likelihood.
With 33 unique site patterns.
Using rescaling scheme : dynamic
Alignment(mydata3bb)
70 taxa
33 sites
33 patterns

Using BEAGLE version: 3.2.0 (PRE-RELEASE) resource 0: CPU
with instance flags: PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_SSE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU
Using ambiguities in tree likelihood.
Ignoring character uncertainty in tree likelihood.
With 33 unique site patterns.
Using rescaling scheme : dynamic

=================================================
Citations for this model:

Bouckaert, Remco, Timothy G. Vaughan, Joëlle Barido-Sottani, Sebastián Duchêne,
Mathieu Fourment, Alexandra Gavryushkina, Joseph Heled et al.
BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis.
PLoS computational biology 15, no. 4 (2019): e1006650.

Raazesh Sainudiin et al. (2004) Microsatellite Mutation Models.
Genetics 168:383-395

Chieh-Hsi Wu and Alexei J. Drummond. (2011) Joint Inference of
Microsatellite Mutation Models, Population History and Genealogies
Using Transdimensional Markov Chain Monte Carlo.
Genetics 188:151-164

===============================================================================
Start likelihood: -32192.51017277799
Warning: Overwriting file mydata3aa.log
Warning: Overwriting file Tree.trees
Sample posterior likelihood prior
0 -32191.4998 -32020.1506 -171.3492 --
2000 -6670.0626 -5937.4861 -732.5765 --
3000 -4051.6884 -3245.7550 -805.9333 --
4000 -3716.2548 -2948.5491 -767.7057 --
5000 -3581.0037 -2815.0593 -765.9443 --
6000 -3008.6556 -2254.0217 -754.6338 --
7000 3124.9009 3873.1857 -748.2847 --
8000 4043.5992 4801.0556 -757.4564 --
9000 6129.3312 6885.8061 -756.4748 --
10000 7098.8272 7853.0255 -754.1983 --
P(posterior) = 6975.571142958615 (was 7098.827207980195) **
P(prior) = -754.1983671222426 (was -754.1983671222426)
P(CoalescentConstant.t:Tree) = -741.2288563351107 (was -741.2288563351107)
P(biasMagnitudePrior.s:Site) = 0.0 (was 0.0)
P(focalPointPrior.s:Site) = -2.639057329615259 (was -2.639057329615259)
P(gPrior.s:Site) = 0.0 (was 0.0)
P(GammaShapePrior.s:Site) = -0.6843872375646877 (was -0.6843872375646877)
P(oneOnA1Prior.s:Site) = 0.0 (was 0.0)
P(PopSizePrior.t:Tree) = -9.646066219951983 (was -9.646066219951983)
P(likelihood) = 7729.769510080858 (was 7853.025575102438) **
P(treeLikelihood.mydata3aa) = -3744.2978001653305 (was -3744.2978001653305)
P(treeLikelihood.mydata3bb) = 11474.067310246188 (was 11474.067310246188)
At sample 10000
Likelihood incorrectly calculated: 7098.827207980195 != 6975.571142958615(123.25606502158007) Operator: Uniform(CoalescentConstantUniformOperator.t:Tree)
11000 7058.6719 7810.9683 -752.2963 6h30m57s/Msamples
12000 15447.7669 16250.4163 -802.6493 6h1m45s/Msamples
13000 16592.6066 17383.5492 -790.9426 5h47m35s/Msamples
14000 25572.7414 26354.0391 -781.2976 5h57m12s/Msamples
15000 35309.2893 36093.4556 -784.1663 5h49m3s/Msamples
16000 36258.9488 37014.1198 -755.1710 5h51m27s/Msamples