Dear Ian, Paolo and David,

Thank you so much for your efforts regarding my inquiry. I would like to 
say that anything that is related to the replicating the analysis that I 
previously posted would be great since I plan to implement them in my 
research, and hopefully, in my PhD thesis. 

Paolo, I will take some time to do more in-depth studying of your paper and 
to see if I can implement those methods on my sample dataset, with the R 
scripts that you have provided.

 

Thank you for your given time and consideration.

 

Sincerely,

Igor 


Dana petak, 4. rujna 2020. u 16:31:31 UTC+2 korisnik [email protected] 
napisao je:

> I Ian and David,
> yes, maybe an ad hoc R package would be great but for reasons not 
> depending on my merits (or de-merits) I'm not (virtually and hoping for 
> some miracles that could bring me again in the research field) on the field 
> of scientific research anymore. So.....only if Antonio Profico and Pasquale 
> Raia will take the commitment to compile the package it will born. 
> Anyway...I can assure all audience here that the functions and the scripts 
> are not difficult to use at all. 
> As we wrote on the supp info all "supplementary material contains 
> necessary R functions and R scripts to reproduce all figures presented in 
> the main text that imply specific analyses. The file "Piras et al Frontiers 
> ancillary functions.r" must be loaded as source. It checks if required 
> packages are installed and loaded and, if not, it calls the corresponding 
> installing and/or loading commands. Any script is intended to work "stand 
> alone" and all landmarks necessary for analyses are defined within the 
> scripts so that no workspace loading is necessary. The ad hoc built 
> functions will be present in a future package that is under development. 
> Some basic functions are wrappers or hacking of functions present in 
> existing packages; others, mainly regarding speed optimization, are 
> inspired by some Stackoverflow comments. Also, function names are not in a 
> "CRAN style" and may change in future."
> All the best
> Paolo
>
>
>
>
> Il giorno ven 4 set 2020 alle ore 16:22 Ian Dworkin <[email protected]> 
> ha scritto:
>
>> Igor and David and Paolo,
>>
>>  Eladio sent me all of the matlab code for those programs,and I have them 
>> on dropbox. I was originally planning on porting it to R, but then Paulo 
>> and I chatted a few months back, and I figured he would make an R package 
>> that among other things included the approach implemented in LORY (among 
>> others) so I figure it would be better for me to be patient for a fully 
>> implemented R library. Not sure if that is in the cards, Paolo?
>>
>> In any case, if this is ok with David and Eladio, I can provide a link to 
>> the matlab code for LORY if that is relevant. What I don't have is the 
>> specific scripts for the examples in the paper itself. 
>>
>> Ian
>>
>> On Fri, 4 Sep 2020 at 10:00, 'David Houle' via Morphmet <
>> [email protected]> wrote:
>>
>>> Dear Igor,
>>>
>>> Thanks for your interest in using Lory.  Lory is purely a visualization 
>>> program, and does not do any statistical testing.  It only performs the 
>>> operations necessary to produce visualizations of the relationships between 
>>> pairs of forms, using whatever configurations of landmarks are furnished to 
>>> the program as input.  The program and documentation is available at 
>>> https://www.bio.fsu.edu/~dhoule/software.html.
>>>
>>> More important though, is how to do similar analyses to those in the 
>>> Márquez et al. (2012)  paper:
>>>
>>> On the example data with *Drosophila* species authors have computed 
>>> sample mean wing shape deformations for the two Drosophila species (Fig. 4).
>>>
>>> Fig. 4 in Márquez et al. (2012) is based on simulated deformations using 
>>> the Drosophila wing mean shape as the origin.  
>>>
>>> o   How did they do that? Did they computed the group means in other 
>>> programs or R packages and then imported them in Lory or there is a way to 
>>> get them in Lory because I haven’t found an option to do that. One of the 
>>> ways, as I see it, is to compute the mean shapes in geomorph and them 
>>> import those means shapes in Lory to visualise those means shapes.
>>>
>>> Yes, you are correct.  Forms that are functions of other forms must be 
>>> calculated outside of Lory, then furnished to Lory.   
>>>
>>>  After one iteration of the Delaunay algorithm, without any selection of 
>>> evaluation  nodes, Lory found 74 nodes for evaluation. Based on that map of 
>>> interspecific differences in local wing shape (Fig.5), on the extracted 
>>> Jacobian determinants (74) ANOVA with Bonferroni correction for multiple 
>>> comparison was performed which resulted with significant (stars) and 
>>> non-significant (crosses) differences.
>>>
>>> o   How did they computed that one shape with displayed interspecific 
>>> differences?
>>>
>>> I believe that Fig. 5 was produced in Lory, by furnishing each 
>>> subcompartment's data to Lory separately.  
>>>
>>> o   Did they extracted Jacobians determinants from Lory and then 
>>> performed ANOVA in some other program?
>>>
>>> Lory does not output the Jacobian determinants directly.  We first 
>>> calculated the determinants in Matlab, then analyzed the differences in 
>>> SAS. 
>>>
>>> o   How did they know which node was significant or not? I suppose that 
>>> you have to extract the coordinates that reflect their position on the map 
>>> of interspecific differences or did I get it wrong?
>>>
>>> Yes, you do local analyses on the sets of determinants that interest 
>>> you. 
>>>
>>>  How did they computed the mean representation of intraspecific variance 
>>> in Drosophila species? In Lory or in other program?
>>>
>>> Again, this is based on simulated data using the Drosophila mean wing 
>>> shape.  Means were calculated in another program, then furnished to Lory.  
>>>
>>>  Figures 7. and 8. represent interspecific correlations and 
>>> interspecific differences and intraspecific variances. I suppose that these 
>>> figures were computed in Coriandis software** on Jacobian determinants? I 
>>> tried to import the data in Coriandis to explore if I could compute and get 
>>> those figures but I am having problems with assigning group info and names 
>>> to the imported non landmark data such as Jacobian determinants – no way I 
>>> could manage to do that even when I tried to follow the footsteps in the 
>>> manual that authors provided.
>>>
>>> The left plots in Fig. 7 were produced in Lory, the right side plots 
>>> were not. Since the bubble plots do not represent shape directly, they are 
>>> not part of Lory.  Eladio Márquez made the bubble plots, and Fig. 8.  
>>>
>>>  
>>>
>>> Eladio Márquez wrote Lory, and performed most of the analyses in the 
>>> Márquez et al. (2012) paper.  He would probably have more insight into 
>>> precisely how some of the Figures you mentioned were produced.   
>>> Unfortunately, this paper was published before journals started to force us 
>>> to furnish all the code necessary to produce the data.  I probably have all 
>>> the programs archived, but these are not clearly documented. As noted in 
>>> the paper, analyses were performed in SAS, Matlab, Java, C++, and Python 
>>> software.  I can dig them out and send them on if you wish.  
>>>
>>>  
>>>
>>> * Márquez, EJ., Cabeen, R., Woods, RP., Houle, D. 2012. The Measurement 
>>> of Local Variation in Shape. Evol Biol, 39: 419 – 439.
>>>
>>> ** Márquez, EJ. & Knowles LL. 2007. Correlated evolution of multivariate 
>>> traits: detecting codivergence across multiple dimensions. J. Evol. Biol., 
>>> 20: 2334 - 2348.
>>>
>>>
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>>> .
>>>
>>
>>
>> -- 
>> Ian Dworkin
>> Department of Biology
>> McMaster University
>> Office phone 905 525 9140 ext. 21775 <(905)%20525-9140>
>> Lab phone 905 525 9140 ext. 20076 <(905)%20525-9140>
>> [email protected]
>> dworkinlab.github.io
>>
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>>
>

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