AA model selection

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laetitia...@berkeley.edu

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Apr 7, 2018, 10:36:50 AM4/7/18
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Good morning!

I am trying to find the best protein substitution model for my AA alignment. I did not make any partitions. Just the whole thing. I used two different commands:

raxmlHPC-PTHREADS -p 12345 -T 12 -m PROTGAMMAAUTO -s alignment.phylip -n AUTO 
raxmlHPC-PTHREADS -p 22345 -T 12 -m PROTGAMMAAUTO --auto-prot=bic -s alignment.phylip -n T1 

The analysis takes about 6h with 12 CPUs. I do not get any errors. However, in the output file I do not see the different likelihood scores for the different protein models. How can I search for them?

I attached the output files below.

Thank you very much for your help.



This is RAxML version 8.2.11 released by Alexandros Stamatakis on June 2017.

With greatly appreciated code contributions by:
Andre Aberer      (HITS)
Simon Berger      (HITS)
Alexey Kozlov     (HITS)
Kassian Kobert    (HITS)
David Dao         (KIT and HITS)
Sarah Lutteropp   (KIT and HITS)
Nick Pattengale   (Sandia)
Wayne Pfeiffer    (SDSC)
Akifumi S. Tanabe (NRIFS)
Charlie Taylor    (UF)


Alignment has 7099 distinct alignment patterns

Proportion of gaps and completely undetermined characters in this alignment: 22.28%

RAxML rapid hill-climbing mode

Using 1 distinct models/data partitions with joint branch length optimization


Executing 1 inferences on the original alignment using 1 distinct randomized MP trees

All free model parameters will be estimated by RAxML
GAMMA model of rate heterogeneity, ML estimate of alpha-parameter

GAMMA Model parameters will be estimated up to an accuracy of 0.1000000000 Log Likelihood units

Partition: 0
Alignment Patterns: 7099
Name: No Name Provided
DataType: AA
Substitution Matrix: AUTO
Using fixed base frequencies




RAxML was called as follows:

/share/eisenlab/gjospin/bin/raxmlHPC-PTHREADS -p 12345 -T 12 -m PROTGAMMAAUTO -s concat.updated.KAMfiltered.phylip -n AUTO 


Partition: 0 with name: No Name Provided


---------------------

This is RAxML version 8.2.11 released by Alexandros Stamatakis on June 2017.

With greatly appreciated code contributions by:
Andre Aberer      (HITS)
Simon Berger      (HITS)
Alexey Kozlov     (HITS)
Kassian Kobert    (HITS)
David Dao         (KIT and HITS)
Sarah Lutteropp   (KIT and HITS)
Nick Pattengale   (Sandia)
Wayne Pfeiffer    (SDSC)
Akifumi S. Tanabe (NRIFS)
Charlie Taylor    (UF)


Alignment has 7099 distinct alignment patterns

Proportion of gaps and completely undetermined characters in this alignment: 22.28%

RAxML rapid hill-climbing mode

Using 1 distinct models/data partitions with joint branch length optimization


Executing 1 inferences on the original alignment using 1 distinct randomized MP trees

All free model parameters will be estimated by RAxML
GAMMA model of rate heterogeneity, ML estimate of alpha-parameter

GAMMA Model parameters will be estimated up to an accuracy of 0.1000000000 Log Likelihood units

Partition: 0
Alignment Patterns: 7099
Name: No Name Provided
DataType: AA
Substitution Matrix: AUTO
Using fixed base frequencies




RAxML was called as follows:

/share/eisenlab/gjospin/bin/raxmlHPC-PTHREADS -p 22345 -T 12 -m PROTGAMMAAUTO --auto-prot=bic -s concat.updated.KAMfiltered.phylip -n T1 


Partition: 0 with name: No Name Provided



Alexandros Stamatakis

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Apr 7, 2018, 3:26:53 PM4/7/18
to ra...@googlegroups.com
I think you analysis must not have terminated yet, I just ran raxml as
follows on a little test dataset:

./raxmlHPC-AVX -p 12345 -m PROTGAMMAAUTO -s ../DATA/prot.phy -n LL1

and obtain the RAxML_info. file output below.

Alexis

RAxML was called as follows:

./raxmlHPC-AVX -p 12345 -m PROTGAMMAAUTO -s ../DATA/prot.phy -n LL1


Partition: 0 with name: No Name Provided
Base frequencies: 0.087 0.044 0.039 0.057 0.019 0.037 0.058 0.083 0.024
0.048 0.086 0.062 0.020 0.038 0.046 0.070 0.061 0.014 0.035 0.071

Automatic protein model assignment algorithm using ML criterion:

Partition: 0 best-scoring AA model: LG likelihood -11004.910506 with
empirical base frequencies


Automatic protein model assignment algorithm using ML criterion:

Partition: 0 best-scoring AA model: LG likelihood -11001.948228 with
empirical base frequencies


Automatic protein model assignment algorithm using ML criterion:

Partition: 0 best-scoring AA model: LG likelihood -11001.794732 with
empirical base frequencies


Automatic protein model assignment algorithm using ML criterion:

Partition: 0 best-scoring AA model: LG likelihood -11001.785752 with
empirical base frequencies


Inference[0]: Time 61.243455 GAMMA-based likelihood -11001.785231, best
rearrangement setting 5


Conducting final model optimizations on all 1 trees under GAMMA-based
models ....

Automatic protein model assignment algorithm using ML criterion:

Partition: 0 best-scoring AA model: LG likelihood -11001.785231 with
empirical base frequencies


Inference[0] final GAMMA-based Likelihood: -11001.785202 tree written to
file /home/stamatak/Desktop/GIT/raxml-hpc/standard-RAxML/RAxML_result.LL1


Starting final GAMMA-based thorough Optimization on tree 0 likelihood
-11001.785202 ....

Final GAMMA-based Score of best tree -11001.785202

Program execution info written to
/home/stamatak/Desktop/GIT/raxml-hpc/standard-RAxML/RAxML_info.LL1
Best-scoring ML tree written to:
/home/stamatak/Desktop/GIT/raxml-hpc/standard-RAxML/RAxML_bestTree.LL1

Overall execution time: 78.448167 secs or 0.021791 hours or 0.000908 days
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www.exelixis-lab.org

Laetitia Georgina Elisabeth Wilkins

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Apr 8, 2018, 8:29:00 AM4/8/18
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Thank you very much Dr. Stamatakis!
Now I know what to do about it. I appreciate the fast reply.

Laetitia

<*))))><       <*))))><                       <*))))><   <*))))><
----------------------------------------------------------------

Laetitia G.E. Wilkins, PhD

SNSF Postdoctoral Research Fellow

Carlson Lab - Evolutionary Ecology of Freshwater Fishes
UC Berkeley, Dept. of Environmental Sciences, Policy & Management

Eisen Lab - Phylogenomics of Novelty
UC Davis, Genome Center 

@M_helvetiae
Wife, mother, researcher
Vice-president Berkeley Spouses, Partners & Parents Association

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Full Professor, Dept. of Informatics, Karlsruhe Institute of Technology

www.exelixis-lab.org
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Laetitia Georgina Elisabeth Wilkins

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May 5, 2018, 2:17:45 PM5/5/18
to ra...@googlegroups.com, alexandros...@gmail.com, Jonathan Eisen, Cassie Ettinger
Good morning Dr. Stamatakis!

I sent you an email pretty much exactly 1 month ago. You helped me fix my command to find the most likely AA substitution model for our large alignment (~20,000 taxa, 37 concatenated genes). 

The command works - no doubt - and I appreciate your help.

However, our server does not. I requested 48 nodes and 3GB RAM and had to wait for 2 weeks to get a slot for this rather big computation on our server. Then, after another 10 days my jobs got cancelled because the bioinformatics core center needed some kind of maintenance. I am back at point zero.

Is there a possibility I could run the model selection on the CIPRES server? I understood from the CIPRES website (https://www.phylo.org/portal2/createTask!changeTab.action?tab=Select+Tool) that I can only infer trees and not just the substitution models. But maybe I misunderstood.

I would like to infer something like this:
raxmlHPC-PTHREADS -p 12345 -T 12 -m PROTGAMMAAUTO -s alignment.phylip -n AUTO 

Is this possible on the CIPRES server?

Thank you so much!
Have a good Saturday.

Laetitia



On Sat, Apr 7, 2018 at 12:26 PM, Alexandros Stamatakis <alexandros...@gmail.com> wrote:
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Full Professor, Dept. of Informatics, Karlsruhe Institute of Technology

www.exelixis-lab.org
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Alexandros Stamatakis

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May 7, 2018, 8:15:35 AM5/7/18
to Laetitia Georgina Elisabeth Wilkins, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger
Dear Laetitia,

The command you specify will just execute a single ML tree search on the
alignment. Is this what you want to do?

As far as CIPRES is concerned, we are not maintaining this service
ourselves, but I have bcced the colleagues at SDSC who are.

Alexis
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>
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>
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Wayne Pfeiffer

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May 7, 2018, 11:41:39 AM5/7/18
to Laetitia Georgina Elisabeth Wilkins, Alexandros Stamatakis, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger, Mark Miller, Wayne Pfeiffer
Hi Laetitia,

The CIPRES gateway *does* support the PROTGAMMAAUTO function. You need to select

. Protein as the Data Type under Simple Parameters
. Protein GAMMA under Advanced Parameters / Protein Analysis Options
. AUTO as the Substitution Model under Advanced Parameters / Protein Analysis Options

* Feel free to give this a try, and let me know if you encounter any problems.

One possible problem is that RAxML sometimes encounters numerical issues and fails for data sets as large as yours. If that is the case, you might try IQ-TREE. It is more stable numerically, but its best trees generally do not have scores as good as those from RAxML. For selecting a model, this may not be of concern.

Good luck!

Wayne

Wayne Pfeiffer

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May 7, 2018, 11:49:21 AM5/7/18
to Laetitia Georgina Elisabeth Wilkins, Alexandros Stamatakis, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger, Mark Miller, Wayne Pfeiffer
Hi Laetitia,

One more thing: analysis of your data set will require more than 80 GB of memory. Thus you also need to select

. I have a data set that may require more than 20 GB of memory

Best regards, Wayne

Laetitia Georgina Elisabeth Wilkins

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May 7, 2018, 11:53:33 AM5/7/18
to Alexandros Stamatakis, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger
Hi Alexis!

From the manual at page 33 I understood that this command will give me a likelihood score for different models. Based on that I can then choose which AA substitution model is most likely. Is that correct?

Is there something missing in my command?

The example below will automatically determine which is the best (the one with the highest likelihood score on the parsimony starting tree) protein substitution model for your dataset using the base frequencies that come with the models. It will chose among the following models: DAYHOFF, DCMUT, JTT, MTREV, WAG, RTREV, CPREV, VT, BLOSUM62, MTMAM, LG, MTART, MTZOA, PMB, HIVB, HIVW, JTTDCMUT, FLU, DUMMY, DUMMY2. These models will not be considered: LG4M, LG4X, PROT_FILE,GTR_UNLINKED, GTR!


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    Full Professor, Dept. of Informatics, Karlsruhe Institute of Technology

    www.exelixis-lab.org <http://www.exelixis-lab.org>



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Alexandros Stamatakis

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May 7, 2018, 12:04:41 PM5/7/18
to Laetitia Georgina Elisabeth Wilkins, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger
Yes, but called like this it will also do a ML tree search ... which is
okay though and serves your purpose

Alexis

On 07.05.2018 18:53, Laetitia Georgina Elisabeth Wilkins wrote:
> Hi Alexis!
>
> From the manual at page 33 I understood that this command will give me
> a likelihood score for different models. Based on that I can then choose
> which AA substitution model is most likely. Is that correct?
>
> Is there something missing in my command?
>
> The example below will automatically determine which is the best (the
> one with the highest likelihood score on the parsimony starting tree)
> protein substitution model for your dataset using the base frequencies
> that come with the models. It will chose among the following models:
> DAYHOFF, DCMUT, JTT, MTREV, WAG, RTREV, CPREV, VT, BLOSUM62, MTMAM, LG,
> MTART, MTZOA, PMB, HIVB, HIVW, JTTDCMUT, FLU, DUMMY, DUMMY2. These
> models will not be considered: LG4M, LG4X, PROT_FILE,GTR_UNLINKED, GTR!
>
>
> On Mon, May 7, 2018 at 5:15 AM, Alexandros Stamatakis
> <alexandros...@gmail.com
> <mailto:alexandros...@gmail.com>> wrote:
>
> Dear Laetitia,
>
> The command you specify will just execute a single ML tree search on
> the alignment. Is this what you want to do?
>
> As far as CIPRES is concerned, we are not maintaining this service
> ourselves, but I have bcced the colleagues at SDSC who are.
>
> Alexis
>
> On 05.05.2018 21:17, Laetitia Georgina Elisabeth Wilkins wrote:
>
> Good morning Dr. Stamatakis!
>
> I sent you an email pretty much exactly 1 month ago. You helped
> me fix my command to find the most likely AA substitution model
> for our large alignment (~20,000 taxa, 37 concatenated genes).
>
> The command works - no doubt - and I appreciate your help.
>
> However, our server does not. I requested 48 nodes and 3GB RAM
> and had to wait for 2 weeks to get a slot for this rather big
> computation on our server. Then, after another 10 days my jobs
> got cancelled because the bioinformatics core center needed some
> kind of maintenance. I am back at point zero.
>
> Is there a possibility I could run the model selection on the
> CIPRES server? I understood from the CIPRES website
> (https://www.phylo.org/portal2/createTask!changeTab.action?tab=Select+Tool
> <https://www.phylo.org/portal2/createTask!changeTab.action?tab=Select+Tool>)
> that I can only infer trees and not just the substitution
> models. But maybe I misunderstood.
>
> I would like to infer something like this:
> raxmlHPC-PTHREADS -p 12345 -T 12 -m PROTGAMMAAUTO -s
> alignment.phylip -n AUTO
>
> Is this possible on the CIPRES server?
>
> Thank you so much!
> Have a good Saturday.
>
> Laetitia
>
>
>
> On Sat, Apr 7, 2018 at 12:26 PM, Alexandros Stamatakis
> <alexandros...@gmail.com
> <mailto:alexandros...@gmail.com>
> <mailto:alexandros...@gmail.com
> <mailto:laetitia...@berkeley.edu>
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>
>
>     --     Alexandros (Alexis) Stamatakis
>
>     Research Group Leader, Heidelberg Institute for Theoretical
> Studies
>     Full Professor, Dept. of Informatics, Karlsruhe Institute
> of Technology
>
> www.exelixis-lab.org <http://www.exelixis-lab.org>
> <http://www.exelixis-lab.org>
>
>
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Laetitia Georgina Elisabeth Wilkins

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May 7, 2018, 12:09:18 PM5/7/18
to Alexandros Stamatakis, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger
Alexis,

one more question with regard to this command:
Where in the output files are the likelihood scores for the different models?
I did not find it in the output file you sent to me.

Thanks.
Laetitia



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             --     Alexandros (Alexis) Stamatakis

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        Studies
             Full Professor, Dept. of Informatics, Karlsruhe Institute
        of Technology

        www.exelixis-lab.org <http://www.exelixis-lab.org>
        <http://www.exelixis-lab.org>


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    Research Group Leader, Heidelberg Institute for Theoretical Studies
    Full Professor, Dept. of Informatics, Karlsruhe Institute of Technology

    www.exelixis-lab.org <http://www.exelixis-lab.org>


Alexandros Stamatakis

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May 8, 2018, 11:41:26 PM5/8/18
to Laetitia Georgina Elisabeth Wilkins, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger
This should be in the RAxML_info file,

Alexis

On 07.05.2018 19:09, Laetitia Georgina Elisabeth Wilkins wrote:
> Alexis,
>
> one more question with regard to this command:
> Where in the output files are the likelihood scores for the different
> models?
> I did not find it in the output file you sent to me.
>
> Thanks.
> Laetitia
>
>
>
> On Mon, May 7, 2018 at 9:04 AM, Alexandros Stamatakis
> <alexandros...@gmail.com
> <mailto:alexandros...@gmail.com>> wrote:
>
> Yes, but called like this it will also do a ML tree search ... which
> is okay though and serves your purpose
>
> Alexis
>
> On 07.05.2018 18:53, Laetitia Georgina Elisabeth Wilkins wrote:
>
> Hi Alexis!
>
>  From the manual at page 33 I understood that this command will
> give me a likelihood score for different models. Based on that I
> can then choose which AA substitution model is most likely. Is
> that correct?
>
> Is there something missing in my command?
>
> The example below will automatically determine which is the best
> (the one with the highest likelihood score on the parsimony
> starting tree) protein substitution model for your dataset using
> the base frequencies that come with the models. It will chose
> among the following models: DAYHOFF, DCMUT, JTT, MTREV, WAG,
> RTREV, CPREV, VT, BLOSUM62, MTMAM, LG, MTART, MTZOA, PMB, HIVB,
> HIVW, JTTDCMUT, FLU, DUMMY, DUMMY2. These models will not be
> considered: LG4M, LG4X, PROT_FILE,GTR_UNLINKED, GTR!
>
>
> On Mon, May 7, 2018 at 5:15 AM, Alexandros Stamatakis
>         <alexandros...@gmail.com
> <mailto:alexandros...@gmail.com>
>         <mailto:alexandros...@gmail.com
> <mailto:alexandros...@gmail.com>>
>         <mailto:alexandros...@gmail.com
> <mailto:alexandros...@gmail.com>
>
>         <mailto:alexandros...@gmail.com
> <mailto:laetitia...@berkeley.edu>
>         <mailto:laetitia...@berkeley.edu
> <mailto:laetitia...@berkeley.edu>>
>              <mailto:laetitia...@berkeley.edu
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>
>
>
>     --     Alexandros (Alexis) Stamatakis
>
>     Research Group Leader, Heidelberg Institute for Theoretical
> Studies
>     Full Professor, Dept. of Informatics, Karlsruhe Institute
> of Technology
>
> www.exelixis-lab.org <http://www.exelixis-lab.org>
> <http://www.exelixis-lab.org>
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Laetitia Georgina Elisabeth Wilkins

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May 9, 2018, 2:56:40 PM5/9/18
to Alexandros Stamatakis, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger
Hi Alexandros!

​This is the info output file before the job got terminated on our server. Can I extract anything useful from it?
On the bottom there are likelihood scores for 6 models, however, I do not see which model is which.

Alignment has 7099 distinct alignment patterns


Proportion of gaps and completely undetermined characters in this alignment: 22.28%


RAxML rapid hill-climbing mode


Using 1 distinct models/data partitions with joint branch length optimization



Executing 1 inferences on the original alignment using 1 distinct randomized MP trees


All free model parameters will be estimated by RAxML

GAMMA model of rate heterogeneity, ML estimate of alpha-parameter


GAMMA Model parameters will be estimated up to an accuracy of 0.1000000000 Log Likelihood units


Partition: 0

Alignment Patterns: 7099

Name: No Name Provided

DataType: AA

Substitution Matrix: AUTO

Using fixed base frequencies





RAxML was called as follows:


/share/eisenlab/gjospin/bin/raxmlHPC-PTHREADS -p 72992345 -T 24 -m PROTGAMMAAUTO -s concat.updated.KAMfiltered.phylip -n AUTO_7_orolo 



Partition: 0 with name: No Name Provided

Base frequencies: 0.087 0.044 0.039 0.057 0.019 0.037 0.058 0.083 0.024 0.048 0.086 0.062 0.020 0.038 0.046 0.070 0.061 0.014 0.035 0.071 


Automatic protein model assignment algorithm using ML criterion:


Partition: 0 best-scoring AA model: LG likelihood -19956802.701780 with fixed base frequencies



Automatic protein model assignment algorithm using ML criterion:


Partition: 0 best-scoring AA model: LG likelihood -19955936.910947 with fixed base frequencies



Automatic protein model assignment algorithm using ML criterion:


Partition: 0 best-scoring AA model: LG likelihood -19955907.359551 with fixed base frequencies



Automatic protein model assignment algorithm using ML criterion:


Partition: 0 best-scoring AA model: LG likelihood -19944415.375817 with fixed base frequencies



Automatic protein model assignment algorithm using ML criterion:


Partition: 0 best-scoring AA model: LG likelihood -19944410.766413 with fixed base frequencies



Automatic protein model assignment algorithm using ML criterion:


Partition: 0 best-scoring AA model: LG likelihood -19940563.520907 with fixed base frequencies



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Alexandros Stamatakis

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May 9, 2018, 2:59:52 PM5/9/18
to Laetitia Georgina Elisabeth Wilkins, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger
yes, that the best model is LG,

alexis
> <mailto:alexandros...@gmail.com>> wrote:
>
> This should be in the RAxML_info file,
>
> Alexis
>
> On 07.05.2018 19:09, Laetitia Georgina Elisabeth Wilkins wrote:
>
> Alexis,
>
> one more question with regard to this command:
> Where in the output files are the likelihood scores for the
> different models?
> I did not find it in the output file you sent to me.
>
> Thanks.
> Laetitia
>
>
>
> On Mon, May 7, 2018 at 9:04 AM, Alexandros Stamatakis
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Laetitia Georgina Elisabeth Wilkins

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May 9, 2018, 3:07:26 PM5/9/18
to Alexandros Stamatakis, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger
1) Why does it give me 6 different scores?

2) Where are the likelihood scores for the other AA substitution models?

Thanks.


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Alexandros Stamatakis

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May 9, 2018, 3:08:50 PM5/9/18
to Laetitia Georgina Elisabeth Wilkins, ra...@googlegroups.com, Jonathan Eisen, Cassie Ettinger


On 09.05.2018 22:07, Laetitia Georgina Elisabeth Wilkins wrote:
> 1) Why does it give me 6 different scores?

as it does a tree search the best AA model is determined each time model
parameters are optimized during the tree search

> 2) Where are the likelihood scores for the other AA substitution models?

they are not shown,

alexis

>
> Thanks.
>
>
> On Wed, May 9, 2018 at 11:59 AM, Alexandros Stamatakis
> <alexandros...@gmail.com
> <mailto:alexandros...@gmail.com>>> wrote:
>
>     This should be in the RAxML_info file,
>
>     Alexis
>
>     On 07.05.2018 19:09, Laetitia Georgina Elisabeth Wilkins wrote:
>
>         Alexis,
>
>         one more question with regard to this command:
>         Where in the output files are the likelihood scores for the
>         different models?
>         I did not find it in the output file you sent to me.
>
>         Thanks.
>         Laetitia
>
>
>
>         On Mon, May 7, 2018 at 9:04 AM, Alexandros Stamatakis
>         <alexandros...@gmail.com
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