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. >> >> >> -- >> You received this message because you are subscribed to the Google Groups >> "Morphmet" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to [email protected]. >> To view this discussion on the web visit >> https://groups.google.com/d/msgid/morphmet2/7c4bfdf0-79a4-50d4-a9a9-20b0b0d77041%40bio.fsu.edu >> <https://groups.google.com/d/msgid/morphmet2/7c4bfdf0-79a4-50d4-a9a9-20b0b0d77041%40bio.fsu.edu?utm_medium=email&utm_source=footer> >> . >> > > > -- > Ian Dworkin > Department of Biology > McMaster University > Office phone 905 525 9140 ext. 21775 > Lab phone 905 525 9140 ext. 20076 > [email protected] > dworkinlab.github.io > > -- > You received this message because you are subscribed to the Google Groups > "Morphmet" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To view this discussion on the web visit > https://groups.google.com/d/msgid/morphmet2/CAGudrjnvkRdBoZePpbASnAvGo4YTY1FMymJEP%2BuxhOGMCtxiDA%40mail.gmail.com > <https://groups.google.com/d/msgid/morphmet2/CAGudrjnvkRdBoZePpbASnAvGo4YTY1FMymJEP%2BuxhOGMCtxiDA%40mail.gmail.com?utm_medium=email&utm_source=footer> > . > -- You received this message because you are subscribed to the Google Groups "Morphmet" group. 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