<p>As it is turned out from the author's words:</p>
<ol>
<li>This is a normal result for the tutorial.</li>
<li>It is recommended to border the deviation of geomodel to 3 powers.</li>
<li>There is set up a homogenous diffusion model but BEAUTi does not show this correctly. Precision is defy τ as bt^-1 where t – a branch length, b – precision. It can be an arbitrary number that the quotient of it divided by the potential tree height would much lower than 1. Otherwise, the next approximation has some deterioration:</li>
</ol>
<p><a href="https://i.sstatic.net/UZFQ7.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/UZFQ7.png" alt="The probability density approximation" /></a></p>
<p>Threshold is an angle (in degrees 0...180) below which there is no contribution to the probability density. The fast check box turns up approximation of arccos of angles close to zero (cos(x) &gt; 0.9). The error is at the most 1e-10. More hidden parameters can be found through XML-editors in prepared files.</p>
<p>By the way, the author, Remco Bouckaert, has released new version recently where we can specify regions for clades explicitly in BEAUTi.</p>
<p>I hope that this information will be useful for anyone like me who is stuck in GEO_SPHERE.</p>

CC BY-SA 4.0
2022-03-16T14:34:56.030Z
Thanks @Vovin it is good to know the underlying spatial model. I'm aware of  recent upgrades, its part of a very active Bayesian group
M__
CC BY-SA 4.0
2022-03-16T14:26:57.853Z
2022-03-16T14:26:57.853Z
Vovin
<p>This may not be the exact answer but its a pretty good guess and suggests an absence of <code>getters</code> and <code>setters</code> for this particular issue. Thus I accept the error does not look informative.</p>
<p>I know 100% what is wrong with the MCMC tree model you performed on HBV, hepatitis B virus.</p>
<p>The <code>ESS</code> are mostly &lt;&lt;200, that is where they are in red. The MCMC needs to run for longer or a simpler model (probably both). For example, the <code>prior</code> is 4 which is way too low.</p>
<p>In particular <code>sprecision.geo</code> is <code>-</code> and that does not look good for the calculation you are performing because it suggests it (the <code>geo</code> object is not present and looks remarkably like the error you are receiving). Simply this will be written in Java and that value it will see as an object. Whether this is singly due to insufficient runtime, I don't know, but the ESS values are a pretty good guess at diagnosing the situation.</p>
<p>What might be happening is that if the values in red are too low and insufficient to calculate <code>sprecision.geo</code> hence its <code>-</code> and the absence of this value is preventing the <code>diffusionModel.s:geo</code> from being calculated.</p>
<p>Do consider Beast is a hugely impressive but complicated population dynamics Bayesian simulation which is further complicated because you are stacking a further level of parameters onto it.</p>
<hr />
<p>I have responded to the comments below here:</p>
<p>HBV is known to be a difficult data set in phylogeny, it has a very weird genome and if further iterations are resulting in errors with the basic MCMC something is definitely not right with the core calculation. 'Too much MCMC' isn't a valid error in a Bayesian calculation. I would simply switch data set and try again. The ESS is simply too low for any further analysis and that's why its in red.</p>
<p>One of the photos provided doesn't seem to stack up.</p>

CC BY-SA 4.0
2022-03-07T19:51:32.310Z
sprecision.geo is "-" because this is a fixed precision parameter (Fig 3) so it does not vary. This was run 1 million iterations as it was specified in the tutorial. As you can check by the link in the question their results are not ideal but certainly better. Moreover, when I run more iterations (10 & 100 millions), I get problems with rate mean and deviation. By the way, the trees were gotten the same topologically & geographically (I am going to apply them to question).
Vovin
CC BY-SA 4.0
2022-03-07T20:18:39.883Z
I've responded above
M__
CC BY-SA 4.0
2022-03-07T21:05:36.393Z
I am trying to reproduce the tutorial and want to distinct the difference between my actions and the author's ones. I made a crack to process the whole sampling [(129 sequences)](https://peerj.com/articles/2406/) but understand that I miss something about geo clock priors. My own research is dedicated to HBA. I have about a half of a thousand our exclusive sequences and about a thousand GenBank ones. So I need to study this instrument in detail before full-blown using.
Vovin
CC BY-SA 4.0
2022-03-07T21:35:55.740Z
The spatial inference depends on and accurate tree.
M__
CC BY-SA 4.0
2022-03-07T19:26:31.803Z
2022-03-07T20:27:53.763Z
2022-03-07T20:27:53.763Z
M__
<p>I have some problems with geosphere package which extends/applies the Beast Bayesian MCMC package for calculating phylogenetic trees. Please, could anyone give any hints about at least one of them?</p>
<p>Firstly, I cannot reproduce <a href="https://github.com/BEAST2-Dev/beast-geo/releases/download/v1.2.0/phylogeography_s.pdf" rel="nofollow noreferrer">the tutorial</a>. I followed the instructions step-by-step but my results are too different (Fig 1) from specified in it. What could I do wrong?
Secondly, it is oft occurred that my mean and standard deviation increase too high (Fig 2). I am aware that this is bad but what is the right way not to allow such situations? Just put an upper border? In this case, what is the reasonable border?
Thirdly, why is a site model of the geodata partition set as the first option in a list of  models for amino acids or nucleotides substitution, &amp; I cannot pick any other (Fig 3 &amp; 4)? What do precision and fast checkbox mean? Is there any way to get under the hood of model to vary more parameters?
Finally, are there any documentation, guides, tutorials &amp;c. about geosphere besides the aforementioned tutorial? I did not find any on its GitHub repository.</p>
<p>Fig 1</p>
<p><a href="https://i.sstatic.net/CNmJM.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/CNmJM.png" alt="Fig 1" /></a></p>
<p>Fig 2</p>
<p><a href="https://i.sstatic.net/EKgEl.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/EKgEl.png" alt="enter image description here" /></a></p>
<p>Fig 3</p>
<p><a href="https://i.sstatic.net/qiK0y.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/qiK0y.png" alt="enter image description here" /></a></p>
<p>Fig 4</p>
<p><a href="https://i.sstatic.net/noenM.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/noenM.png" alt="enter image description here" /></a></p>
<p>My trees:</p>
<p><a href="https://i.sstatic.net/1gUwc.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/1gUwc.jpg" alt="trees in DensiTree" /></a></p>
<p><a href="https://i.sstatic.net/bS4Uh.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/bS4Uh.jpg" alt="Consensus tree in Google Earth" /></a></p>

<phylogenetics><phylogeny><virus><beast>
How to use GEO_SPHERE?
# How to use GEO_SPHERE?

(Asked by: username_0 on 2022-03-07)

I have some problems with geosphere package which extends/applies the Beast Bayesian MCMC package for calculating phylogenetic trees. Please, could anyone give any hints about at least one of them?

Firstly, I cannot reproduce [the tutorial](https://github.com/BEAST2-Dev/beast-geo/releases/download/v1.2.0/phylogeography_s.pdf). I followed the instructions step-by-step but my results are too different (Fig 1) from specified in it. What could I do wrong?
Secondly, it is oft occurred that my mean and standard deviation increase too high (Fig 2). I am aware that this is bad but what is the right way not to allow such situations? Just put an upper border? In this case, what is the reasonable border?
Thirdly, why is a site model of the geodata partition set as the first option in a list of models for amino acids or nucleotides substitution, & I cannot pick any other (Fig 3 & 4)? What do precision and fast checkbox mean? Is there any way to get under the hood of model to vary more parameters?
Finally, are there any documentation, guides, tutorials &c. about geosphere besides the aforementioned tutorial? I did not find any on its GitHub repository.

Fig 1

[![Fig 1](https://i.sstatic.net/CNmJM.png)](https://i.sstatic.net/CNmJM.png)

Fig 2

[![enter image description here](https://i.sstatic.net/EKgEl.png)](https://i.sstatic.net/EKgEl.png)

Fig 3

[![enter image description here](https://i.sstatic.net/qiK0y.png)](https://i.sstatic.net/qiK0y.png)

Fig 4

[![enter image description here](https://i.sstatic.net/noenM.png)](https://i.sstatic.net/noenM.png)

My trees:

[![trees in DensiTree](https://i.sstatic.net/1gUwc.jpg)](https://i.sstatic.net/1gUwc.jpg)

[![Consensus tree in Google Earth](https://i.sstatic.net/bS4Uh.jpg)](https://i.sstatic.net/bS4Uh.jpg)

**Tags:** phylogenetics, phylogeny, virus, beast

---

## 2 answers

### Answer by username_0 on 2022-03-16. Score: 1 | Accepted answer

As it is turned out from the author's words:

1. This is a normal result for the tutorial.
2. It is recommended to border the deviation of geomodel to 3 powers.
3. There is set up a homogenous diffusion model but BEAUTi does not show this correctly. Precision is defy τ as bt^-1 where t – a branch length, b – precision. It can be an arbitrary number that the quotient of it divided by the potential tree height would much lower than 1. Otherwise, the next approximation has some deterioration:

[![The probability density approximation](https://i.sstatic.net/UZFQ7.png)](https://i.sstatic.net/UZFQ7.png)

Threshold is an angle (in degrees 0...180) below which there is no contribution to the probability density. The fast check box turns up approximation of arccos of angles close to zero (cos(x) > 0.9). The error is at the most 1e-10. More hidden parameters can be found through XML-editors in prepared files.

By the way, the author, Remco Bouckaert, has released new version recently where we can specify regions for clades explicitly in BEAUTi.

I hope that this information will be useful for anyone like me who is stuck in GEO\_SPHERE.

> **Comments:**
> **username_1**: Thanks @Vovin it is good to know the underlying spatial model. I'm aware of  recent upgrades, its part of a very active Bayesian group  

---

### Answer by username_1 on 2022-03-07. Score: 0

This may not be the exact answer but its a pretty good guess and suggests an absence of `getters` and `setters` for this particular issue. Thus I accept the error does not look informative.

I know 100% what is wrong with the MCMC tree model you performed on HBV, hepatitis B virus.

The `ESS` are mostly <<200, that is where they are in red. The MCMC needs to run for longer or a simpler model (probably both). For example, the `prior` is 4 which is way too low.

In particular `sprecision.geo` is `-` and that does not look good for the calculation you are performing because it suggests it (the `geo` object is not present and looks remarkably like the error you are receiving). Simply this will be written in Java and that value it will see as an object. Whether this is singly due to insufficient runtime, I don't know, but the ESS values are a pretty good guess at diagnosing the situation.

What might be happening is that if the values in red are too low and insufficient to calculate `sprecision.geo` hence its `-` and the absence of this value is preventing the `diffusionModel.s:geo` from being calculated.

Do consider Beast is a hugely impressive but complicated population dynamics Bayesian simulation which is further complicated because you are stacking a further level of parameters onto it.

---

I have responded to the comments below here:

HBV is known to be a difficult data set in phylogeny, it has a very weird genome and if further iterations are resulting in errors with the basic MCMC something is definitely not right with the core calculation. 'Too much MCMC' isn't a valid error in a Bayesian calculation. I would simply switch data set and try again. The ESS is simply too low for any further analysis and that's why its in red.

One of the photos provided doesn't seem to stack up.

> **Comments:**
> **username_0**: sprecision.geo is "-" because this is a fixed precision parameter (Fig 3) so it does not vary. This was run 1 million iterations as it was specified in the tutorial. As you can check by the link in the question their results are not ideal but certainly better. Moreover, when I run more iterations (10 & 100 millions), I get problems with rate mean and deviation. By the way, the trees were gotten the same topologically & geographically (I am going to apply them to question).  
> **username_1**: I've responded above  
> **username_0**: I am trying to reproduce the tutorial and want to distinct the difference between my actions and the author's ones. I made a crack to process the whole sampling [(129 sequences)](https://peerj.com/articles/2406/) but understand that I miss something about geo clock priors. My own research is dedicated to HBA. I have about a half of a thousand our exclusive sequences and about a thousand GenBank ones. So I need to study this instrument in detail before full-blown using.  
> **username_1**: The spatial inference depends on and accurate tree.  

---

